Yang, C.Y.[Chun-Yu],
Zhou, J.[Jie],
Non-stationary data sequence classification using online class priors
estimation,
PR(41), No. 8, August 2008, pp. 2656-2664.
Elsevier DOI
0805
Concept drift; Online classification; EM
BibRef
Zhang, Z.H.[Zhi-Hao],
Zhou, J.[Jie],
Transfer estimation of evolving class priors in data stream
classification,
PR(43), No. 9, September 2010, pp. 3151-3161.
Elsevier DOI
1006
Concept drift; Transfer learning; Prior estimation
BibRef
Gao, X.B.[Xin-Bo],
Wang, X.M.[Xiu-Mei],
Li, X.L.[Xue-Long],
Tao, D.C.[Da-Cheng],
Transfer latent variable model based on divergence analysis,
PR(44), No. 10-11, October-November 2011, pp. 2358-2366.
Elsevier DOI
1101
Dimensionality reduction; Latent variable model; Transfer learning;
Bregman divergence
BibRef
Pang, J.,
Huang, Q.,
Yan, S.,
Jiang, S.,
Qin, L.,
Transferring Boosted Detectors Towards Viewpoint and Scene Adaptiveness,
IP(20), No. 5, May 2011, pp. 1388-1400.
IEEE DOI
1104
Training set isn't exactly the same as test data.
BibRef
di Carlo, S.,
Falasconi, M.,
Sanchez, E.,
Scionti, A.,
Squillero, G.,
Tonda, A.,
Increasing pattern recognition accuracy for chemical sensing by
evolutionary based drift compensation,
PRL(32), No. 13, 1 October 2011, pp. 1594-1603.
Elsevier DOI
1109
Sensor drift; Evolutionary strategy; Classification systems
BibRef
Gonçalves, Jr., P.M.[Paulo Mauricio],
Maior de Barros, R.S.[Roberto Souto],
RCD: A recurring concept drift framework,
PRL(34), No. 9, July 2013, pp. 1018-1025.
Elsevier DOI
1305
Data streams; Concept drift; Recurring contexts; On-line learning;
Multivariate non-parametric statistical test
BibRef
Salakhutdinov, R.[Ruslan],
Tenenbaum, J.B.[Joshua B.],
Torralba, A.B.[Antonio B.],
Learning with Hierarchical-Deep Models,
PAMI(35), No. 8, 2013, pp. 1958-1971.
IEEE DOI
1307
BibRef
Earlier: A1, A3, A2:
Learning to share visual appearance for multiclass object detection,
CVPR11(1481-1488).
IEEE DOI
1106
Bayesian methods; Deep networks.
Rare objects "borrow" statistical info from related common objects.
Learn hierarchy of objects.
BibRef
Lin, D.[Di],
An, X.[Xing],
Zhang, J.[Jian],
Double-bootstrapping source data selection for instance-based transfer
learning,
PRL(34), No. 11, 1 August 2013, pp. 1279-1285.
Elsevier DOI
1306
Transfer learning; Instance-based transfer learning; Source
data selection; Bagging
BibRef
Varga, R.,
Nedevschi, S.,
Label Transfer by Measuring Compactness,
IP(22), No. 12, 2013, pp. 4711-4723.
IEEE DOI
1312
feature extraction
BibRef
Li, Q.[Qing],
Chen, X.[Xiaowu],
Song, Y.[Yafei],
Zhang, Y.,
Jin, X.[Xin],
Zhao, Q.P.[Qin-Ping],
Geodesic Propagation for Semantic Labeling,
IP(23), No. 11, November 2014, pp. 4812-4825.
IEEE DOI
1410
BibRef
Earlier: A2, A1, A3, A5, A6, Only:
Supervised Geodesic Propagation for Semantic Label Transfer,
ECCV12(III: 553-565).
Springer DOI
1210
Image color analysis
BibRef
Khamis, S.[Sameh],
Lampert, C.H.[Christoph H.],
CoConut: Co-Classification with Output Space Regularization,
BMVC14(xx-yy).
HTML Version.
1410
Jointly classifying multiple, otherwise independent, data samples.
BibRef
Fang, M.[Min],
Guo, Y.[Yong],
Zhang, X.S.[Xiao-Song],
Li, X.[Xiao],
Multi-source transfer learning based on label shared subspace,
PRL(51), No. 1, 2015, pp. 101-106.
Elsevier DOI
1412
Transfer learning
BibRef
Sun, C.[Chao],
Bao, B.K.[Bing-Kun],
Xu, C.S.[Chang-Sheng],
Knowing Verb From Object:
Retagging With Transfer Learning on Verb-Object Concept Images,
MultMed(17), No. 10, October 2015, pp. 1747-1759.
IEEE DOI
1511
Bayes methods
BibRef
Xu, Y.,
Fang, X.,
Wu, J.,
Li, X.,
Zhang, D.,
Discriminative Transfer Subspace Learning via Low-Rank and Sparse
Representation,
IP(25), No. 2, February 2016, pp. 850-863.
IEEE DOI
1601
Adaptation models
BibRef
Deng, C.,
Tang, X.,
Yan, J.,
Liu, W.,
Gao, X.,
Discriminative Dictionary Learning With Common Label Alignment for
Cross-Modal Retrieval,
MultMed(18), No. 2, February 2016, pp. 208-218.
IEEE DOI
1601
Correlation
BibRef
Mudunuri, S.P.[Sivaram Prasad],
Biswas, S.[Soma],
A coupled discriminative dictionary and transformation learning
approach with applications to cross domain matching,
PRL(71), No. 1, 2016, pp. 38-44.
Elsevier DOI
1602
Face recognition
BibRef
Mandal, D.,
Biswas, S.[Soma],
Generalized Coupled Dictionary Learning Approach With Applications to
Cross-Modal Matching,
IP(25), No. 8, August 2016, pp. 3826-3837.
IEEE DOI
1608
Correlation
BibRef
Das, N.,
Mandal, D.,
Biswas, S.[Soma],
Simultaneous Semi-Coupled Dictionary Learning for Matching in
Canonical Space,
IP(26), No. 8, August 2017, pp. 3995-4004.
IEEE DOI
1707
BibRef
Earlier:
Simultaneous Semi-Coupled Dictionary Learning for Matching RGBD Data,
Biometrics16(243-251)
IEEE DOI
1612
computer vision, image matching, image representation,
Mahalanobis metric, canonical representation, canonical space,
computer vision, cross-modal recognition,
simultaneous semicoupled dictionary learning,
sparse coefficients, Computer vision, Couplings, Dictionaries,
Linear programming, Measurement, Testing, Training,
Cross-modal matching, RGBD data, audio-image data,
privileged information, text-image, data
BibRef
An, T.H.[Taeg-Hyun],
Hong, K.S.[Ki-Sang],
Label transfer via sparse representation,
PRL(70), No. 1, 2016, pp. 1-7.
Elsevier DOI
1602
Scene parsing
BibRef
Zhang, L.[Lei],
Zuo, W.M.[Wang-Meng],
Zhang, D.,
LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation,
IP(25), No. 3, March 2016, pp. 1177-1191.
IEEE DOI
1602
Big Data
BibRef
Zhou, S.[Shuang],
Smirnov, E.[Evgueni],
Schoenmakers, G.[Gijs],
Driessens, K.[Kurt],
Peeters, R.[Ralf],
Testing exchangeability for transfer decision,
PRL(88), No. 1, 2017, pp. 64-71.
Elsevier DOI
1703
Instance-transfer learning
BibRef
Shoeleh, F.[Farzaneh],
Asadpour, M.[Masoud],
Graph based skill acquisition and transfer Learning for continuous
reinforcement learning domains,
PRL(87), No. 1, 2017, pp. 104-116.
Elsevier DOI
1703
Reinforcement learning
BibRef
Wang, J.[Jie],
Luo, C.[Chang],
Huang, H.Q.[Han-Qiao],
Zhao, H.Z.[Hui-Zhen],
Wang, S.Q.[Shi-Qiang],
Transferring Pre-Trained Deep CNNs for Remote Scene Classification
with General Features Learned from Linear PCA Network,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Qi, G.J.,
Liu, W.,
Aggarwal, C.,
Huang, T.,
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or
Unseen Classes,
PAMI(39), No. 7, July 2017, pp. 1360-1373.
IEEE DOI
1706
Bridges, Noise measurement, Semantics, Training, Transfer functions,
Videos, Visualization, Multimodal analysis, image classification,
intermodal and intramodal label transfers (I2LT), zero-shot, learning
BibRef
Wang, J.[Jun],
Wang, G.Q.[Guo-Qing],
Li, L.[Leida],
Image Pattern Similarity Index and Its Application to Task-Specific
Transfer Learning,
IEICE(E100-D), No. 12, December 2017, pp. 3032-3035.
WWW Link.
1712
BibRef
Gao, N.N.[Neng-Neng],
Huang, S.J.[Sheng-Jun],
Yan, Y.F.[Yi-Fan],
Chen, S.C.[Song-Can],
Cross modal similarity learning with active queries,
PR(75), No. 1, 2018, pp. 214-222.
Elsevier DOI
1712
Active learning
BibRef
Zhang, B.C.[Bao-Chang],
Perina, A.[Alessandro],
Li, C.[Ce],
Ye, Q.X.[Qi-Xiang],
Murino, V.[Vittorio],
Del Bue, A.[Alessio],
Manifold constraint transfer for visual structure-driven optimization,
PR(77), 2018, pp. 87-98.
Elsevier DOI
1802
Manifold, Transfer learning,
Alternating direction method of multipliers, Object tracking,
Object categorization
BibRef
Kumar, S.[Suren],
Dhiman, V.[Vikas],
Koch, P.A.[Parker A.],
Corso, J.J.[Jason J.],
Learning Compositional Sparse Bimodal Models,
PAMI(40), No. 5, May 2018, pp. 1032-1044.
IEEE DOI
1804
Transfer from, e.g., red triangles/blue squares to
red squares/blue triangles.
Dictionaries, Encoding, Poles and towers, Robot sensing systems,
Semantics, Visualization, Multimodal learning,
tabletop robotics
BibRef
Zheng, F.[Feng],
Tang, Y.[Yi],
Shao, L.[Ling],
Hetero-Manifold Regularisation for Cross-Modal Hashing,
PAMI(40), No. 5, May 2018, pp. 1059-1071.
IEEE DOI
1804
Data models, Euclidean distance, Hamming distance, Manifolds,
Semantics, Support vector machines, Training, Cross-modal hashing,
manifold regularisation
BibRef
Zhu, F.[Fan],
Shao, L.[Ling],
Tang, J.[Jun],
Boosted Cross-Domain Categorization,
BMVC14(xx-yy).
HTML Version.
1410
BibRef
Chang, H.[Hang],
Han, J.[Ju],
Zhong, C.[Cheng],
Snijders, A.M.[Antoine M.],
Mao, J.H.[Jian-Hua],
Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse
Coding for Biomedical Applications,
PAMI(40), No. 5, May 2018, pp. 1182-1194.
IEEE DOI
1804
Biological neural networks, Convolutional codes, Encoding,
Feature extraction, Knowledge engineering, Training,
sharable information
BibRef
Peng, P.X.[Pei-Xi],
Tian, Y.H.[Yong-Hong],
Xiang, T.[Tao],
Wang, Y.W.[Yao-Wei],
Pontil, M.[Massimiliano],
Huang, T.J.[Tie-Jun],
Joint Semantic and Latent Attribute Modelling for Cross-Class
Transfer Learning,
PAMI(40), No. 7, July 2018, pp. 1625-1638.
IEEE DOI
1806
Adaptation models, Computational modeling, Data models,
Dictionaries, Semantics, Training, Visualization, Attribute learning,
zero-shot learning
BibRef
Guo, X.[Xin],
Wang, S.[Song],
Tie, Y.[Yun],
Qi, L.[Lin],
Guan, L.[Ling],
Joint intermodal and intramodal correlation preservation for
semi-paired learning,
PR(81), 2018, pp. 36-49.
Elsevier DOI
1806
Semi-paired learning, Canonical correlation analysis, Clustering
BibRef
Shi, Q.,
Liu, X.,
Huang, X.,
An Active Relearning Framework for Remote Sensing Image
Classification,
GeoRS(56), No. 6, June 2018, pp. 3468-3486.
IEEE DOI
1806
Adaptation models, Convergence, Feature extraction, Remote sensing,
Spectral analysis, Training, Uncertainty, Active learning (AL),
relearning
BibRef
Han, W.[Wei],
Feng, R.[Ruyi],
Wang, L.Z.[Li-Zhe],
Cheng, Y.F.[Ya-Fan],
A semi-supervised generative framework with deep learning features
for high-resolution remote sensing image scene classification,
PandRS(145), 2018, pp. 23-43.
Elsevier DOI
1810
Scene classification, Deep learning, Self-label,
High resolution remote sensing images
BibRef
Ding, Z.,
Fu, Y.,
Dual Low-Rank Decompositions for Robust Cross-View Learning,
IP(28), No. 1, January 2019, pp. 194-204.
IEEE DOI
1810
Manifolds, Robustness, Feature extraction, Face, Task analysis,
Data models, Sensors, Cross-view learning, low-rank modeling, graph embedding
BibRef
Ma, Z.C.[Zhong-Chen],
Chen, S.C.[Song-Can],
Ma, D.[Di],
Heterogeneous multi-output classification by structured conditional
risk minimization,
PRL(116), 2018, pp. 50-57.
Elsevier DOI
1812
Multi-output classification, Problem transformation,
Output structures, Heterogeneity, Structured prediction
BibRef
Duan, L.J.[Li-Juan],
En, Q.[Qing],
Qiao, Y.H.[Yuan-Hua],
Cui, S.[Song],
Qing, L.Y.[Lai-Yun],
Deep feature representation based on privileged knowledge transfer,
PRL(119), 2019, pp. 62-70.
Elsevier DOI
1902
Feature representation, Privileged knowledge transfer,
Deep neural network, Multi-object retrieval
BibRef
Shi, Q.[Qian],
Zhang, Y.[Yipeng],
Liu, X.P.[Xiao-Ping],
Zhao, K.[Kefei],
Regularised transfer learning for hyperspectral image classification,
IET-CV(13), No. 2, March 2019, pp. 188-193.
DOI Link
1902
BibRef
Tang, X.Y.[Xin-Yao],
Du, B.[Bo],
Huang, J.Z.[Jian-Zhong],
Wang, Z.[Zengmao],
Zhang, L.F.[Le-Fei],
On combining active and transfer learning for medical data
classification,
IET-CV(13), No. 2, March 2019, pp. 194-205.
DOI Link
1902
BibRef
Luo, Y.[Yong],
Wen, Y.G.[Yong-Gang],
Liu, T.L.[Tong-Liang],
Tao, D.C.[Da-Cheng],
Transferring Knowledge Fragments for Learning Distance Metric from a
Heterogeneous Domain,
PAMI(41), No. 4, April 2019, pp. 1013-1026.
IEEE DOI
1903
Measurement, Task analysis, Face, Visualization, Feature extraction,
Training, Pattern recognition, Transfer learning,
nonlinear
BibRef
Deng, C.[Cheng],
Xue, Y.M.[Yu-Meng],
Liu, X.L.[Xiang-Long],
Li, C.[Chao],
Tao, D.C.[Da-Cheng],
Active Transfer Learning Network: A Unified Deep Joint
Spectral-Spatial Feature Learning Model for Hyperspectral Image
Classification,
GeoRS(57), No. 3, March 2019, pp. 1741-1754.
IEEE DOI
1903
feature extraction, geophysical image processing,
image classification, learning (artificial intelligence),
transfer learning (TL)
BibRef
Ji, R.R.[Rong-Rong],
Gao, Y.[Yue],
Hong, R.C.[Ri-Chang],
Liu, Q.[Qiong],
Tao, D.C.[Da-Cheng],
Li, X.L.[Xue-Long],
Spectral-Spatial Constraint Hyperspectral Image Classification,
GeoRS(52), No. 3, March 2014, pp. 1811-1824.
IEEE DOI
1403
hyperspectral imaging
BibRef
Luo, F.[Fulin],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
Zhang, L.F.[Le-Fei],
Tao, D.C.[Da-Cheng],
Feature Learning Using Spatial-Spectral Hypergraph Discriminant
Analysis for Hyperspectral Image,
Cyber(49), No. 7, July 2019, pp. 2406-2419.
IEEE DOI
1905
Feature extraction, Laplace equations, Learning systems,
Cybernetics, Hyperspectral imaging, Image reconstruction,
spatial-spectral information
BibRef
Basavaraju, S.[Sathisha],
Gaj, S.[Sibaji],
Sur, A.[Arijit],
Object Memorability Prediction using Deep Learning:
Location and Size Bias,
JVCIR(59), 2019, pp. 117-127.
Elsevier DOI
1903
Object Memorability, Deep Learning, Transfer Learning
BibRef
Ye, R.[Rui],
Dai, Q.[Qun],
Li, M.[MeiLing],
A hybrid transfer learning algorithm incorporating TrSVM with GASEN,
PR(92), 2019, pp. 192-202.
Elsevier DOI
1905
Transfer learning, Ensemble selection,
Genetic Algorithm based Selective Ensemble algorithm (GASEN),
Transfer Learning algorithm incorporating TrSVM with GASEN (TrGASVM)
BibRef
Wang, C.[Chao],
Tuo, H.[Hongya],
Wang, J.X.[Jie-Xin],
Qiao, L.F.[Ling-Feng],
Discriminative transfer learning via local and global structure
preservation,
SIViP(13), No. 4, June 2019, pp. 753-760.
Springer DOI
1906
BibRef
Zhang, J.[Jing],
Li, W.Q.[Wan-Qing],
Ogunbona, P.[Philip],
Xu, D.[Dong],
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition:
A Problem-Oriented Perspective,
Surveys(51), No. 1, February 2019, pp. Article No 7.
DOI Link
1906
Survey, Transfer Learning.
BibRef
Xue, S.[Shan],
Lu, J.[Jie],
Zhang, G.Q.[Guang-Quan],
Cross-domain network representations,
PR(94), 2019, pp. 135-148.
Elsevier DOI
1906
Network representation, Transfer learning, Random walk,
Information network, Unsupervised learning, Feature learning
BibRef
Yu, X.[Xu],
Jiang, F.[Feng],
Du, J.W.[Jun-Wei],
Gong, D.W.[Dun-Wei],
A cross-domain collaborative filtering algorithm with expanding user
and item features via the latent factor space of auxiliary domains,
PR(94), 2019, pp. 96-109.
Elsevier DOI
1906
Cross-domain collaborative filtering, Feature expansion,
Funk-SVD decomposition, Classification, Latent factor space
BibRef
Rostami, M.[Mohammad],
Kolouri, S.[Soheil],
Eaton, E.[Eric],
Kim, K.[Kyungnam],
Deep Transfer Learning for Few-Shot SAR Image Classification,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Hong, D.,
Yokoya, N.,
Chanussot, J.,
Zhu, X.X.,
CoSpace: Common Subspace Learning From Hyperspectral-Multispectral
Correspondences,
GeoRS(57), No. 7, July 2019, pp. 4349-4359.
IEEE DOI
1907
Hyperspectral imaging, Optimization, Satellites, Earth, Manifolds,
Common subspace learning (CoSpace), cross-modality learning,
remote sensing
BibRef
Chen, W.,
Hsu, T.H.,
Tsai, Y.H.,
Chen, M.,
Wang, Y.F.,
Transfer Neural Trees: Semi-Supervised Heterogeneous Domain
Adaptation and Beyond,
IP(28), No. 9, Sep. 2019, pp. 4620-4633.
IEEE DOI
1908
image classification, learning (artificial intelligence),
pattern classification, trees (mathematics),
zero-shot learning
BibRef
Tan, M.[Min],
Yu, J.[Jun],
Zhang, H.Y.[Hong-Yuan],
Rui, Y.[Yong],
Tao, D.C.[Da-Cheng],
Image Recognition by Predicted User Click Feature With Multidomain
Multitask Transfer Deep Network,
IP(28), No. 12, December 2019, pp. 6047-6062.
IEEE DOI
1909
Image recognition, Task analysis, Visualization, Predictive models,
Adaptation models, Correlation, Computational modeling,
word embedding
BibRef
Yan, C.,
Li, L.,
Zhang, C.,
Liu, B.,
Zhang, Y.,
Dai, Q.,
Cross-Modality Bridging and Knowledge Transferring for Image
Understanding,
MultMed(21), No. 10, October 2019, pp. 2675-2685.
IEEE DOI
1910
feature extraction, image classification, image representation,
learning (artificial intelligence), multimedia systems,
knowledge transferring
BibRef
Li, X.H.[Xu-Hong],
Grandvalet, Y.[Yves],
Davoine, F.[Franck],
A baseline regularization scheme for transfer learning with
convolutional neural networks,
PR(98), 2020, pp. 107049.
Elsevier DOI
1911
Transfer learning, Regularization, Convolutional networks
BibRef
Sanodiya, R.K.[Rakesh Kumar],
Mathew, J.[Jimson],
A novel unsupervised Globality-Locality Preserving Projections in
transfer learning,
IVC(90), 2019, pp. 103802.
Elsevier DOI
1912
Discriminant analysis, Transfer learning, Domain adaptation,
Manifold, Classification, Unsupervised learning, Dimensionality reduction
BibRef
Han, N.,
Wu, J.,
Fang, X.,
Xie, S.,
Zhan, S.,
Xie, K.,
Li, X.,
Latent Elastic-Net Transfer Learning,
IP(29), 2020, pp. 2820-2833.
IEEE DOI
2001
Transfer learning, elastic-net, source domain, target domain, machine learning
BibRef
Pires de Lima, R.[Rafael],
Marfurt, K.[Kurt],
Convolutional Neural Network for Remote-Sensing Scene Classification:
Transfer Learning Analysis,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Zhang, B.,
Yang, W.,
Wang, Z.,
Zhuo, L.,
Han, J.,
Zhen, X.,
The Structure Transfer Machine: Theory and Applications,
IP(29), 2020, pp. 2889-2902.
IEEE DOI
2002
Manifolds, Deep learning, Training, Probabilistic logic,
Object tracking, Task analysis, Transfer learning,
learning theory
BibRef
Das, D.,
Lee, C.S.G.,
A Two-Stage Approach to Few-Shot Learning for Image Recognition,
IP(29), 2020, pp. 3336-3350.
IEEE DOI
2002
Transfer learning, convolutional neural network,
few-shot learning, image classification
BibRef
Gholenji, E.[Elahe],
Tahmoresnezhad, J.[Jafar],
Joint local and statistical discriminant learning via feature alignment,
SIViP(14), No. 3, April 2020, pp. 609-616.
Springer DOI
2004
Machine learning applied to unseen items. Domain shift.
BibRef
Peng, Z.,
Zhang, W.,
Han, N.,
Fang, X.,
Kang, P.,
Teng, L.,
Active Transfer Learning,
CirSysVideo(30), No. 4, April 2020, pp. 1022-1036.
IEEE DOI
2004
Task analysis, Kernel, Bicycles, Linear programming,
Machine learning, Training, Optimization, Negative transfer,
information diversity
BibRef
Bae, J.H.[Ji-Hoon],
Yeo, D.[Doyeob],
Yim, J.[Junho],
Kim, N.S.[Nae-Soo],
Pyo, C.S.[Cheol-Sig],
Kim, J.[Junmo],
Densely Distilled Flow-Based Knowledge Transfer in Teacher-Student
Framework for Image Classification,
IP(29), 2020, pp. 5698-5710.
IEEE DOI
2005
BibRef
Earlier: A2, A1, A5, A3, A4, A6:
Sequential Knowledge Transfer in Teacher-Student Framework Using
Densely Distilled Flow-Based Information,
ICIP18(674-678)
IEEE DOI
1809
Knowledge transfer, Training, Computational modeling, Data mining,
Optimization, Image classification, Computer architecture,
residual network.
Training, Data mining, Optimization, Image classification,
Knowledge transfer, Computational modeling, Reliability,
BibRef
Dong, R.M.[Run-Min],
Li, C.[Cong],
Fu, H.[Haohuan],
Wang, J.[Jie],
Li, W.[Weijia],
Yao, Y.[Yi],
Gan, L.[Lin],
Yu, L.[Le],
Gong, P.[Peng],
Improving 3-m Resolution Land Cover Mapping through Efficient
Learning from an Imperfect 10-m Resolution Map,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link
2005
BibRef
Liu, W.,
Qin, R.,
A MultiKernel Domain Adaptation Method for Unsupervised Transfer
Learning on Cross-Source and Cross-Region Remote Sensing Data
Classification,
GeoRS(58), No. 6, June 2020, pp. 4279-4289.
IEEE DOI
2005
Domain adaptation (DA), image classification, remote sensing,
stable index, transfer learning (TL), unsupervised learning
BibRef
Lu, Y.[Ying],
Luo, L.[Lingkun],
Huang, D.[Di],
Wang, Y.H.[Yun-Hong],
Chen, L.M.[Li-Ming],
Knowledge Transfer in Vision Recognition: A Survey,
Surveys(53), No. 2, April 2020, pp. xx-yy.
DOI Link
2007
vision recognition, computer vision, transfer learning,
Knowledge transfer, machine learning
BibRef
Geng, J.,
Deng, X.,
Ma, X.,
Jiang, W.,
Transfer Learning for SAR Image Classification Via Deep Joint
Distribution Adaptation Networks,
GeoRS(58), No. 8, August 2020, pp. 5377-5392.
IEEE DOI
2007
Radar polarimetry, Probability distribution,
Synthetic aperture radar, Training, Task analysis,
transfer learning
BibRef
Zhou, J.H.[Jian-Hang],
Zeng, S.N.[Shao-Ning],
Zhang, B.[Bob],
Two-stage knowledge transfer framework for image classification,
PR(107), 2020, pp. 107529.
Elsevier DOI
2008
Image classification, Teacher-student model,
Two-stage classification, Sparse representation
BibRef
Tamaazousti, Y.[Youssef],
Le Borgne, H.[Hervé],
Hudelot, C.[Céline],
Seddik, M.E.A.[Mohamed-El-Amine],
Tamaazousti, M.[Mohamed],
Learning More Universal Representations for Transfer-Learning,
PAMI(42), No. 9, September 2020, pp. 2212-2224.
IEEE DOI
2008
Task analysis, Visualization, Measurement, Semantics, Additives, Veins,
Training, Universal representations, universality evaluation,
visual recognition
BibRef
Wu, X.[Xiang],
He, R.[Ran],
Hu, Y.[Yibo],
Sun, Z.N.[Zhe-Nan],
Learning an Evolutionary Embedding via Massive Knowledge Distillation,
IJCV(128), No. 8-9, September 2020, pp. 2089-2106.
Springer DOI
2008
transferring knowledge from a large powerful teacher network to a
small compact student one.
BibRef
Yan, X.T.[Xue-Ting],
Misra, I.[Ishan],
Gupta, A.[Abhinav],
Ghadiyaram, D.[Deepti],
Mahajan, D.[Dhruv],
ClusterFit: Improving Generalization of Visual Representations,
CVPR20(6508-6517)
IEEE DOI
2008
Pre-training.
Task analysis, Training, Feature extraction, Visualization, Videos,
Tagging, Twitter
BibRef
Wang, Y.,
Chen, X.,
You, Y.,
Li, L.E.,
Hariharan, B.,
Campbell, M.,
Weinberger, K.Q.,
Chao, W.,
Train in Germany, Test in the USA:
Making 3D Object Detectors Generalize,
CVPR20(11710-11720)
IEEE DOI
2008
Laser radar, Automobiles, Detectors,
Object detection, Cameras, Training
BibRef
Passalis, N.[Nikolaos],
Tzelepi, M.[Maria],
Tefas, A.[Anastasios],
Heterogeneous Knowledge Distillation Using Information Flow Modeling,
CVPR20(2336-2345)
IEEE DOI
2008
From complex teacher to smaller student.
Training, Neural networks, Knowledge engineering, Data models,
Convergence, Data mining, Transforms
BibRef
Bhattacharjee, B.,
Render, J.R.,
Hill, M.,
Dube, P.,
Huo, S.,
Glass, M.R.,
Belgodere, B.,
Pankanti, S.,
Codella, N.,
Watson, P.,
P2L: Predicting Transfer Learning for Images and Semantic Relations,
DeepVision20(3284-3293)
IEEE DOI
2008
Task analysis, Training, Computational modeling, Data models,
Machine learning, Adaptation models, Semantics
BibRef
Zhong, Y.,
Maki, A.,
Regularizing CNN Transfer Learning With Randomised Regression,
CVPR20(13634-13643)
IEEE DOI
2008
Task analysis, Training, Image representation, Computer vision,
Adaptation models, Neurons, Data models
BibRef
Yan, X.,
Acuna, D.,
Fidler, S.,
Neural Data Server:
A Large-Scale Search Engine for Transfer Learning Data,
CVPR20(3892-3901)
IEEE DOI
2008
Servers, Data models, Task analysis, Computational modeling,
Search engines, Training, Machine learning
BibRef
Kim, Y.,
Soh, J.W.,
Park, G.Y.,
Cho, N.I.,
Transfer Learning From Synthetic to Real-Noise Denoising With
Adaptive Instance Normalization,
CVPR20(3479-3489)
IEEE DOI
2008
Training, Noise level, Noise reduction, Convolution, Cameras,
Pipelines, Image reconstruction
BibRef
Royer, A.,
Lampert, C.H.,
A Flexible Selection Scheme for Minimum-Effort Transfer Learning,
WACV20(2180-2189)
IEEE DOI
2006
Task analysis, Training, Tuning, Feature extraction, Visualization,
Knowledge engineering, Training data
BibRef
Lamb, A.[Alex],
Ozair, S.[Sherjil],
Verma, V.[Vikas],
Ha, D.[David],
SketchTransfer: A Challenging New Task for Exploring
Detail-Invariance and the Abstractions Learned by Deep Networks,
WACV20(952-961)
IEEE DOI
2006
Domain transfer applied to sketch recognition. Result are not great.
Training, Task analysis, Cats, Dogs, Automobiles, Perturbation methods, Ear
BibRef
Li, J.,
Xu, Z.,
Wang, Y.,
Zhao, Q.,
Kankanhalli, M.S.,
GradMix: Multi-source Transfer across Domains and Tasks,
WACV20(3008-3016)
IEEE DOI
2006
Task analysis, Training, Adaptation models, Silicon, Computer vision,
Optimization, Training data
BibRef
Bi, S.[Sai],
Sunkavalli, K.[Kalyan],
Perazzi, F.[Federico],
Shechtman, E.[Eli],
Kim, V.[Vladimir],
Ramamoorthi, R.[Ravi],
Deep CG2Real: Synthetic-to-Real Translation via Image Disentanglement,
ICCV19(2730-2739)
IEEE DOI
2004
Train on synthetic.
image processing, learning (artificial intelligence),
two-stage pipeline, improved CycleGAN network, Training
BibRef
Tran, A.T.[Anh Tuan],
Nguyen, C.[Cuong],
Hassner, T.[Tal],
Transferability and Hardness of Supervised Classification Tasks,
ICCV19(1395-1405)
IEEE DOI
2004
entropy, face recognition, image classification,
learning (artificial intelligence), object recognition,
Computational modeling
BibRef
Wu, Y.W.[Yuan-Wei],
Zhang, Z.M.[Zi-Ming],
Wang, G.H.[Guang-Hui],
Unsupervised Deep Feature Transfer for Low Resolution Image
Classification,
RLQ19(1065-1069)
IEEE DOI
2004
data structures, feature extraction, image classification,
image enhancement, image resolution, neural nets,
low resolution image classificatin
BibRef
Li, K.,
Zhang, Y.,
Li, K.,
Li, Y.,
Fu, Y.,
Attention Bridging Network for Knowledge Transfer,
ICCV19(5197-5206)
IEEE DOI
2004
image segmentation, learning (artificial intelligence),
neural nets, pattern classification, classification network,
Knowledge transfer
BibRef
Kuen, J.,
Perazzi, F.,
Lin, Z.,
Zhang, J.,
Tan, Y.,
Scaling Object Detection by Transferring Classification Weights,
ICCV19(6043-6052)
IEEE DOI
2004
feature extraction, genomics, image classification,
information retrieval, learning (artificial intelligence),
Knowledge engineering
BibRef
Huang, H.,
Jain, V.,
Mehta, H.,
Ku, A.,
Magalhaes, G.,
Baldridge, J.,
Ie, E.,
Transferable Representation Learning in Vision-and-Language
Navigation,
ICCV19(7403-7412)
IEEE DOI
2004
computer vision, image sequences,
learning (artificial intelligence), Length measurement
BibRef
Han, K.,
Vedaldi, A.,
Zisserman, A.,
Learning to Discover Novel Visual Categories via Deep Transfer
Clustering,
ICCV19(8400-8408)
IEEE DOI
2004
image classification, learning (artificial intelligence),
object recognition, pattern clustering, known classes, Dogs
BibRef
Durall, R.,
Pfreundt, F.,
Keuper, J.,
Semi Few-Shot Attribute Translation,
IVCNZ19(1-8)
IEEE DOI
2004
image processing, learning (artificial intelligence),
semifew-shot attribute translation, image-to-image translation,
generative transfer learning
BibRef
Iqbal, A.,
Richard, A.,
Gall, J.,
Enhancing Temporal Action Localization with Transfer Learning from
Action Recognition,
CoView19(1533-1540)
IEEE DOI
2004
feature extraction, image classification, image motion analysis,
image segmentation, image sequences, inference mechanisms, Action Detection
BibRef
Liu, B.,
Wu, Z.,
Hu, H.,
Lin, S.,
Deep Metric Transfer for Label Propagation with Limited Annotated
Data,
MDALC19(1317-1326)
IEEE DOI
2004
Code, Learning.
WWW Link. image annotation, object recognition, unsupervised learning,
deep metric transfer, limited annotated data, object class,
self supervised learning
BibRef
Jakubovitz, D.,
Rodrigues, M.R.D.,
Giryes, R.,
Lautum Regularization for Semi-Supervised Transfer Learning,
SDL-CV19(763-767)
IEEE DOI
2004
information theory, learning (artificial intelligence),
neural nets, source dataset, deep neural network, Information Theory
BibRef
Cicek, S.,
Soatto, S.,
Unsupervised Domain Adaptation via Regularized Conditional Alignment,
ICCV19(1416-1425)
IEEE DOI
2004
pattern classification, statistical distributions,
unsupervised learning, classifier performance, Neural networks
BibRef
Dwivedi, K.[Kshitij],
Roig, G.[Gemma],
Representation Similarity Analysis for Efficient Task Taxonomy and
Transfer Learning,
CVPR19(12379-12388).
IEEE DOI
2002
BibRef
Wang, Z.[Zirui],
Dai, Z.[Zihang],
Poczos, B.[Barnabas],
Carbonell, J.[Jaime],
Characterizing and Avoiding Negative Transfer,
CVPR19(11285-11294).
IEEE DOI
2002
BibRef
Ahn, S.S.[Sung-Soo],
Hu, S.X.[Shell Xu],
Damianou, A.[Andreas],
Lawrence, N.D.[Neil D.],
Dai, Z.W.[Zhen-Wen],
Variational Information Distillation for Knowledge Transfer,
CVPR19(9155-9163).
IEEE DOI
2002
BibRef
Herath, S.[Samitha],
Harandi, M.[Mehrtash],
Fernando, B.[Basura],
Nock, R.[Richard],
Min-Max Statistical Alignment for Transfer Learning,
CVPR19(9280-9289).
IEEE DOI
2002
BibRef
Chen, Y.C.[Yun-Chun],
Lin, Y.Y.[Yen-Yu],
Yang, M.H.[Ming-Hsuan],
Huang, J.B.[Jia-Bin],
CrDoCo: Pixel-Level Domain Transfer With Cross-Domain Consistency,
CVPR19(1791-1800).
IEEE DOI
2002
BibRef
Gong, R.[Rui],
Li, W.[Wen],
Chen, Y.H.[Yu-Hua],
Van Gool, L.J.[Luc J.],
DLOW: Domain Flow for Adaptation and Generalization,
CVPR19(2472-2481).
IEEE DOI
2002
BibRef
Li, Y.S.[Yun-Sheng],
Vasconcelos, N.M.[Nuno M.],
Efficient Multi-Domain Learning by Covariance Normalization,
CVPR19(5419-5428).
IEEE DOI
2002
BibRef
Essich, M.[Michael],
Ludl, D.[Dennis],
Gulde, T.[Thomas],
Curio, C.[Cristóbal],
Learning to Translate Between Real World and Simulated 3D Sensors
While Transferring Task Models,
3DV19(681-689)
IEEE DOI
1911
Real data not like trained data
Sensors, Data models, Task analysis, Adaptation models,
Training, Character Animation
BibRef
Minami, S.[Soma],
Yamashita, T.[Takayoshi],
Fujiyoshi, H.[Hironobu],
Gradual Sampling Gate for Bidirectional Knowledge Distillation,
MVA19(1-6)
DOI Link
1911
Transfer knowledge from large pre-trained network to smaller one.
data compression, learning (artificial intelligence),
neural nets, gradual sampling gate,
Power markets
BibRef
Coors, B.[Benjamin],
Condurache, A.P.[Alexandru Paul],
Geiger, A.[Andreas],
NoVA: Learning to See in Novel Viewpoints and Domains,
3DV19(116-125)
IEEE DOI
1911
Adaptation models, Task analysis, Estimation, Semantics,
Image segmentation, Cameras, Geometry, Novel Viewpoint Adaptation,
Viewpoint Invariance
BibRef
Bao, Y.,
Li, Y.,
Huang, S.,
Zhang, L.,
Zheng, L.,
Zamir, A.,
Guibas, L.J.[Leonidas J.],
An Information-Theoretic Approach to Transferability in Task Transfer
Learning,
ICIP19(2309-2313)
IEEE DOI
1910
Task transfer learning, Transferability, H-Score,
Image recognition & classification
BibRef
Zhu, Y.[Yi],
Xue, J.[Jia],
Newsam, S.[Shawn],
Gated Transfer Network for Transfer Learning,
ACCV18(IV:354-369).
Springer DOI
1906
BibRef
Kim, J.[Jaekyum],
Koh, J.[Junho],
Kim, Y.[Yecheol],
Choi, J.[Jaehyung],
Hwang, Y.[Youngbae],
Choi, J.W.[Jun Won],
Robust Deep Multi-modal Learning Based on Gated Information Fusion
Network,
ACCV18(IV:90-106).
Springer DOI
1906
BibRef
Zhong, Y.[Yang],
Li, V.[Vladimir],
Okada, R.[Ryuzo],
Maki, A.[Atsuto],
Target Aware Network Adaptation for Efficient Representation Learning,
CEFR-LCV18(IV:450-467).
Springer DOI
1905
Finding the CNN that works.
BibRef
Okatani, T.[Takayuki],
Liu, X.[Xing],
Suganuma, M.[Masanori],
Improving Generalization Ability of Deep Neural Networks for Visual
Recognition Tasks,
CCIW19(3-13).
Springer DOI
1905
BibRef
Sawatzky, J.[Johann],
Garbade, M.[Martin],
Gall, J.[Juergen],
Ex Paucis Plura: Learning Affordance Segmentation from Very Few
Examples,
GCPR18(169-184).
Springer DOI
1905
Use existing annotated datasets to annotate new ones (reduce what needs
more work).
BibRef
Sayed, N.[Nawid],
Brattoli, B.[Biagio],
Ommer, B.[Björn],
Cross and Learn: Cross-Modal Self-supervision,
GCPR18(228-243).
Springer DOI
1905
BibRef
Rahman, M.M.[Mohammad Mahfujur],
Fookes, C.[Clinton],
Baktashmotlagh, M.[Mahsa],
Sridharan, S.[Sridha],
Multi-Component Image Translation for Deep Domain Generalization,
WACV19(579-588)
IEEE DOI
1904
image classification, learning (artificial intelligence),
neural nets, protocols, protocol, synthetic images,
Adaptation models
BibRef
Chen, D.,
Liang, X.,
Wang, Y.,
Gao, W.,
Soft Transfer Learning via Gradient Diagnosis for Visual Relationship
Detection,
WACV19(1118-1126)
IEEE DOI
1904
inference mechanisms, learning (artificial intelligence),
object detection, optimisation, diverse language ambiguities,
Dogs
BibRef
Wang, T.,
Huan, J.,
Zhu, M.,
Instance-Based Deep Transfer Learning,
WACV19(367-375)
IEEE DOI
1904
computer vision, image classification,
learning (artificial intelligence),
Load modeling
BibRef
Li, J.S.[Jian-Shu],
Zhou, P.[Pan],
Chen, Y.P.[Yun-Peng],
Zhao, J.[Jian],
Roy, S.[Sujoy],
Yan, S.C.[Shui-Cheng],
Feng, J.S.[Jia-Shi],
Sim, T.[Terence],
Task Relation Networks,
WACV19(932-940)
IEEE DOI
1904
covariance matrices, learning (artificial intelligence),
task analysis, task covariance modeling,
Heuristic algorithms
See also Estimation of Affective Level in the Wild with Multiple Memory Networks.
BibRef
Zhang, Y.[Ying],
Xiang, T.[Tao],
Hospedales, T.M.[Timothy M.],
Lu, H.C.[Hu-Chuan],
Deep Mutual Learning,
CVPR18(4320-4328)
IEEE DOI
1812
Training, Computational modeling, Task analysis,
Supervised learning, Optimization, Entropy, Neural networks
BibRef
Kundu, J.N.[Jogendra Nath],
Uppala, P.K.[Phani Krishna],
Pahuja, A.[Anuj],
Babu, R.V.[R. Venkatesh],
AdaDepth: Unsupervised Content Congruent Adaptation for Depth
Estimation,
CVPR18(2656-2665)
IEEE DOI
1812
Task analysis, Estimation, Semantics, Adaptation models, Training,
Predictive models.
BibRef
Lee, K.,
He, X.,
Zhang, L.,
Yang, L.,
CleanNet: Transfer Learning for Scalable Image Classifier Training
with Label Noise,
CVPR18(5447-5456)
IEEE DOI
1812
Noise measurement, Feature extraction, Training, Task analysis,
Neural networks, Labeling, Manuals
BibRef
Zamir, A.R.,
Sax, A.,
Cheerla, N.,
Suri, R.,
Cao, Z.,
Malik, J.,
Guibas, L.J.,
Robust Learning Through Cross-Task Consistency,
CVPR20(11194-11203)
IEEE DOI
2008
Task analysis, Training, Image edge detection, Neural networks,
Computer vision, Uncertainty
BibRef
Zamir, A.R.,
Sax, A.,
Shen, W.,
Guibas, L.J.[Leonidas J.],
Malik, J.,
Savarese, S.,
Taskonomy: Disentangling Task Transfer Learning,
CVPR18(3712-3722)
IEEE DOI
1812
Task analysis, Computational modeling, Taxonomy, Dictionaries
BibRef
Chen, S.,
Zhang, C.,
Dong, M.,
Coupled End-to-End Transfer Learning with Generalized Fisher
Information,
CVPR18(4329-4338)
IEEE DOI
1812
Task analysis, Training, Decoding, Neural networks,
Adaptation models, Image reconstruction, Feature extraction
BibRef
Huang, X.,
Peng, Y.,
Deep Cross-Media Knowledge Transfer,
CVPR18(8837-8846)
IEEE DOI
1812
Media, Training, Correlation, Semantics, Adaptation models,
Knowledge transfer, Computational modeling
BibRef
Noroozi, M.,
Vinjimoor, A.,
Favaro, P.,
Pirsiavash, H.,
Boosting Self-Supervised Learning via Knowledge Transfer,
CVPR18(9359-9367)
IEEE DOI
1812
Task analysis, Computer architecture, Computational modeling,
Training, Feature extraction, Data models, Measurement
BibRef
Mormont, R.,
Geurts, P.,
Marée, R.,
Comparison of Deep Transfer Learning Strategies for Digital Pathology,
Microscopy18(2343-234309)
IEEE DOI
1812
Feature extraction, Task analysis, Biomedical imaging, Training,
Support vector machines, Computer vision
BibRef
Lu, W.,
Chung, F.,
A Deep Graphical Model for Layered Knowledge Transfer,
ICPR18(260-265)
IEEE DOI
1812
Task analysis, Dictionaries, Adaptation models,
Inference algorithms, Graphical models, Training
BibRef
Passalis, N.,
Tefas, A.,
Neural Network Knowledge Transfer using Unsupervised Similarity
Matching,
ICPR18(716-721)
IEEE DOI
1812
a
Receivers, Knowledge transfer, Training, Knowledge engineering,
Neural networks, Computational modeling, Geometry
BibRef
Wu, Y.X.[Yu-Xin],
He, K.[Kaiming],
Group Normalization,
ECCV18(XIII: 3-19).
Springer DOI
1810
BibRef
Pan, X.G.[Xin-Gang],
Luo, P.[Ping],
Shi, J.P.[Jian-Ping],
Tang, X.[Xiaoou],
Two at Once: Enhancing Learning and Generalization Capacities via
IBN-Net,
ECCV18(II: 484-500).
Springer DOI
1810
Instance normalization and batch normalization for expanding domain.
BibRef
Hou, S.H.[Sai-Hui],
Pan, X.Y.[Xin-Yu],
Loy, C.C.[Chen Change],
Wang, Z.L.[Zi-Lei],
Lin, D.H.[Da-Hua],
Lifelong Learning via Progressive Distillation and Retrospection,
ECCV18(III: 452-467).
Springer DOI
1810
BibRef
Huang, H.S.[Hao-Shuo],
Huang, Q.X.[Qi-Xing],
Krähenbühl, P.[Philipp],
Domain Transfer Through Deep Activation Matching,
ECCV18(XVI: 611-626).
Springer DOI
1810
BibRef
Tao, Q.Y.[Qing-Yi],
Yang, H.[Hao],
Cai, J.F.[Jian-Fei],
Zero-Annotation Object Detection with Web Knowledge Transfer,
ECCV18(XI: 387-403).
Springer DOI
1810
BibRef
Pintea, S.L.[Silvia L.],
Liu, Y.[Yue],
van Gemert, J.C.[Jan C.],
Recurrent Knowledge Distillation,
ICIP18(3393-3397)
IEEE DOI
1809
small network learns from larger network.
Computational modeling, Memory management, Training, Color,
Convolution, Road transportation, Knowledge distillation,
recurrent layers
BibRef
Paul, A.[Angshuman],
Majumdar, A.[Angshul],
Mukherjee, D.P.[Dipti Prasad],
Discriminative Autoencoder,
ICIP18(3049-3053)
IEEE DOI
1809
Minimization, Linear programming, Training, Encoding,
Biomedical imaging, Decoding, Autoencoder, discriminative,
cross-dataset
BibRef
Inoue, T.,
Choudhury, S.,
De Magistris, G.,
Dasgupta, S.,
Transfer Learning from Synthetic to Real Images Using Variational
Autoencoders for Precise Position Detection,
ICIP18(2725-2729)
IEEE DOI
1809
Lighting, Training, Task analysis, Robots, Decoding,
Image color analysis, Cameras, deep learning, position detection,
computer simulation
BibRef
Liu, X.,
Wang, C.,
Hu, Y.,
Zeng, Z.,
Bai, J.,
Liao, G.,
Transfer Learning with Convolutional Neural Network for Early Gastric
Cancer Classification on Magnifiying Narrow-Band Imaging Images,
ICIP18(1388-1392)
IEEE DOI
1809
Feature extraction, Task analysis, Computer architecture, Cancer,
Training, Sensitivity, Convolutional neural networks,
convolutional neural networks (CNNs)
BibRef
Bai, T.,
Yang, J.,
Chen, J.,
Guo, X.,
Huang, X.,
Yao, Y.,
Double-Task Deep Q-Learning with Multiple Views,
CEFR-LCV17(1050-1058)
IEEE DOI
1802
Aerospace electronics, Cameras, Robot kinematics,
Robot vision systems, Training
BibRef
Chang, J.H.R.[J.H. Rick],
Li, C.L.[Chun-Liang],
Póczos, B.[Barnabás],
Kumar, B.V.K.V.[B. V. K. Vijaya],
One Network to Solve Them All:
Solving Linear Inverse Problems Using Deep Projection Models,
ICCV17(5889-5898)
IEEE DOI
1802
compressed sensing, image restoration, inverse problems,
iterative methods, learning (artificial intelligence),
Signal resolution
BibRef
Li, D.,
Yang, Y.,
Song, Y.Z.,
Hospedales, T.M.,
Deeper, Broader and Artier Domain Generalization,
ICCV17(5543-5551)
IEEE DOI
1802
learning (artificial intelligence),
DG alternatives, DG benchmark dataset, DG methods, benchmarks,
Painting
BibRef
Kim, K.I.[Kwang In],
Tompkin, J.[James],
Richardt, C.[Christian],
Predictor Combination at Test Time,
ICCV17(3573-3581)
IEEE DOI
1802
differential geometry, image denoising,
learning (artificial intelligence), prediction theory,
Training
BibRef
Aygün, M.,
Aytar, Y.,
Ekenel, H.K.,
Exploiting Convolution Filter Patterns for Transfer Learning,
TASKCV17(2674-2680)
IEEE DOI
1802
Analytical models, Computer architecture, Convolution,
Covariance matrices, Detectors, Training
BibRef
Devi, V.S.[V. Sowmini],
Padmanabhan, V.[Vineet],
Pujari, A.K.[Arun K.],
A Matrix Factorization & Clustering Based Approach for Transfer
Learning,
PReMI17(77-83).
Springer DOI
1711
BibRef
Aljundi, R.[Rahaf],
Chakravarty, P.[Punarjay],
Tuytelaars, T.[Tinne],
Expert Gate: Lifelong Learning with a Network of Experts,
CVPR17(7120-7129)
IEEE DOI
1711
Data models, Load modeling, Logic gates, Neural networks, Training,
Training, data
BibRef
Zhang, J.,
Li, W.,
Ogunbona, P.,
Joint Geometrical and Statistical Alignment for Visual Domain
Adaptation,
CVPR17(5150-5158)
IEEE DOI
1711
Image recognition, Linear programming, Minimization,
Pattern recognition, Training, Visualization
BibRef
Ge, W.,
Yu, Y.,
Borrowing Treasures from the Wealthy:
Deep Transfer Learning through Selective Joint Fine-Tuning,
CVPR17(10-19)
IEEE DOI
1711
Kernel, Machine learning, Neural networks, Training data, Visualization
BibRef
Yim, J.,
Joo, D.,
Bae, J.,
Kim, J.,
A Gift from Knowledge Distillation: Fast Optimization, Network
Minimization and Transfer Learning,
CVPR17(7130-7138)
IEEE DOI
1711
Feature extraction, Knowledge engineering,
Knowledge transfer, Optimization, Training
BibRef
Yu, L.J.[Liang-Jiang],
Fan, G.L.[Guo-Liang],
Rare Class Oriented Scene Labeling Using CNN Incorporated Label
Transfer,
ISVC16(I: 309-320).
Springer DOI
1701
BibRef
Gupta, S.[Saurabh],
Hoffman, J.[Judy],
Malik, J.[Jitendra],
Cross Modal Distillation for Supervision Transfer,
CVPR16(2827-2836)
IEEE DOI
1612
BibRef
Littwin, E.,
Wolf, L.,
Complexity of multiverse networks and their multilayer generalization,
ICPR16(372-377)
IEEE DOI
1705
Complexity theory, Feeds, Joining processes, Neural networks,
Nonhomogeneous media, Training, Upper, bound
BibRef
Littwin, E.,
Wolf, L.,
The Multiverse Loss for Robust Transfer Learning,
CVPR16(3957-3966)
IEEE DOI
1612
BibRef
Sharmanska, V.,
Quadrianto, N.,
Learning from the Mistakes of Others:
Matching Errors in Cross-Dataset Learning,
CVPR16(3967-3975)
IEEE DOI
1612
BibRef
Chu, B.[Brian],
Madhavan, V.[Vashisht],
Beijbom, O.[Oscar],
Hoffman, J.[Judy],
Darrell, T.J.[Trevor J.],
Best Practices for Fine-Tuning Visual Classifiers to New Domains,
TASKCV16(III: 435-442).
Springer DOI
1611
Fine tuned generic to specific domain.
BibRef
Heravi, E.J.[Elnaz Jahani],
Aghdam, H.H.[Hamed Habibi],
Puig, D.[Domenec],
Training a Mentee Network by Transferring Knowledge from a Mentor
Network,
TASKCV16(III: 500-507).
Springer DOI
1611
BibRef
Yan, Y.G.[Yu-Guang],
Wu, Q.Y.[Qing-Yao],
Tan, M.[Mingkui],
Min, H.Q.[Hua-Qing],
Online Heterogeneous Transfer Learning by Weighted Offline and Online
Classifiers,
TASKCV16(III: 467-474).
Springer DOI
1611
BibRef
Sun, B.,
Peng, X.C.[Xing-Chao],
Yu, S.X.,
Saenko, K.,
Ground2sky label transfer for fine-grained aerial car recognition,
ICIP17(360-364)
IEEE DOI
1803
Automobiles, Google, Image color analysis, Image recognition,
Image resolution, Object recognition, Task analysis,
Label Transfer
BibRef
Peng, X.C.[Xing-Chao],
Hoffman, J.,
Yu, S.X.,
Saenko, K.[Kate],
Fine-to-coarse knowledge transfer for low-res image classification,
ICIP16(3683-3687)
IEEE DOI
1610
Automobiles
BibRef
Irie, G.[Go],
Arai, H.[Hiroyuki],
Taniguchi, Y.[Yukinobu],
Alternating Co-Quantization for Cross-Modal Hashing,
ICCV15(1886-1894)
IEEE DOI
1602
Binary codes
BibRef
Shkodrani, S.[Sindi],
Hofmann, M.[Michael],
Gavves, E.[Efstratios],
Dynamic Adaptation on Non-stationary Visual Domains,
TASKCV18(II:158-171).
Springer DOI
1905
BibRef
Gavves, E.,
Mensink, T.,
Tommasi, T.,
Snoek, C.G.M.,
Tuytelaars, T.,
Active Transfer Learning with Zero-Shot Priors:
Reusing Past Datasets for Future Tasks,
ICCV15(2731-2739)
IEEE DOI
1602
Computer vision
BibRef
Paul, A.,
Rottensteiner, F.,
Heipke, C.,
Transfer Learning Based on Logistic Regression,
CMRT15(145-152).
DOI Link
1602
BibRef
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Domain Adaptation .