Xiang, C.,
Zhang, L.,
Tang, Y.,
Zou, W.,
Xu, C.,
MS-CapsNet: A Novel Multi-Scale Capsule Network,
SPLetters(25), No. 12, December 2018, pp. 1850-1854.
IEEE DOI
1812
feature extraction, image classification, image representation,
network theory (graphs), image classification,
deep learning
BibRef
Zhu, K.Q.[Kai-Qiang],
Chen, Y.S.[Yu-Shi],
Ghamisi, P.[Pedram],
Jia, X.P.[Xiu-Ping],
Benediktsson, J.A.[Jón Atli],
Deep Convolutional Capsule Network for Hyperspectral Image Spectral
and Spectral-Spatial Classification,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Jia, S.[Sen],
Lin, Z.J.[Zhi-Jie],
Xu, M.[Meng],
Huang, Q.[Qiang],
Zhou, J.[Jun],
Jia, X.P.[Xiu-Ping],
Li, Q.Q.[Qing-Quan],
A Lightweight Convolutional Neural Network for Hyperspectral Image
Classification,
GeoRS(59), No. 5, May 2021, pp. 4150-4163.
IEEE DOI
2104
Hyperspectral imaging, Feature extraction, Convolution,
Convolutional neural networks, Deep learning,
hyperspectral imagery
BibRef
Rosario, V.M.d.,
Borin, E.,
Breternitz, M.,
The Multi-Lane Capsule Network,
SPLetters(26), No. 7, July 2019, pp. 1006-1010.
IEEE DOI
1906
convolutional neural nets, learning (artificial intelligence),
parallel processing, multilane capsule network, MLCN,
CNN
BibRef
Paoletti, M.E.[Mercedes E.],
Haut, J.M.[Juan M.],
Fernandez-Beltran, R.,
Plaza, J.[Javier],
Plaza, A.J.[Antonio J.],
Li, J.[Jun],
Pla, F.[Filiberto],
Capsule Networks for Hyperspectral Image Classification,
GeoRS(57), No. 4, April 2019, pp. 2145-2160.
IEEE DOI
1904
convolutional neural nets, hyperspectral imaging,
image classification, learning (artificial intelligence),
hyperspectral imaging (HSI)
See also Deep Pyramidal Residual Networks for Spectral-Spatial Hyperspectral Image Classification.
BibRef
Ding, X.,
Wang, N.,
Gao, X.,
Li, J.,
Wang, X.,
Liu, T.,
Group Feedback Capsule Network,
IP(29), 2020, pp. 6789-6799.
IEEE DOI
2007
Routing, Neurons, Transforms, Heuristic algorithms, Convolution, Nose,
Capsule networks, network architecture design
BibRef
Mandal, B.[Bodhisatwa],
Sarkhel, R.[Ritesh],
Ghosh, S.[Swarnendu],
Das, N.[Nibaran],
Nasipuri, M.[Mita],
Two-phase Dynamic Routing for Micro and Macro-level Equivariance in
Multi-Column Capsule Networks,
PR(109), 2021, pp. 107595.
Elsevier DOI
2009
Dynamic routing, Routing by agreement, Multi-level,
Multi-column neural network, Capsule networks
BibRef
Amira, O.[Ouafa],
Xu, S.[Shuang],
Du, F.[Fang],
Zhang, J.[Jiangshe],
Zhang, C.X.[Chun-Xia],
Hamza, R.[Rafik],
Weighted-capsule routing via a fuzzy gaussian model,
PRL(138), 2020, pp. 424-430.
Elsevier DOI
1806
Capsule network, Deep learning, Image classification,
Weighted capsule fuzzy gaussian model, Pose loss
BibRef
Xiang, C.,
Wang, Z.,
Tian, S.,
Liao, J.,
Zou, W.,
Xu, C.,
Matrix Capsule Convolutional Projection for Deep Feature Learning,
SPLetters(27), 2020, pp. 1899-1903.
IEEE DOI
2011
Task analysis, Object detection, Training, Convolution, Semantics,
Mathematical model, Encoding, Capsule network, classification,
orthogonal projection
BibRef
Zhang, S.F.[Suo-Fei],
Fan, W.H.[Wen-Hao],
Wu, X.F.[Xiao-Fu],
Towards capsule routing as reconstruction with sparsity constraints,
PRL(140), 2020, pp. 193-199.
Elsevier DOI
2012
Capsule networks, Dynamic routing, Deep learning
BibRef
Li, Y.Q.[Yue-Qiao],
Su, H.[Hang],
Zhu, J.[Jun],
AdvCapsNet: To defense adversarial attacks based on Capsule networks,
JVCIR(75), 2021, pp. 103037.
Elsevier DOI
2103
Capsule, Adversarial, Defense, Robustness
BibRef
Peer, D.[David],
Stabinger, S.[Sebastian],
Rodríguez-Sánchez, A.[Antonio],
Limitation of capsule networks,
PRL(144), 2021, pp. 68-74.
Elsevier DOI
2103
Capsule networks, Deep learning, Limitation, Universal approximator
BibRef
Ding, X.H.[Xiao-Hui],
Li, Y.[Yong],
Yang, J.[Ji],
Li, H.P.[Hua-Peng],
Liu, L.J.[Ling-Jia],
Liu, Y.X.Y.[Yang-Xiao-Yue],
Zhang, C.[Ce],
An Adaptive Capsule Network for Hyperspectral Remote Sensing
Classification,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Tan, X.[Xiong],
Xue, Z.X.[Zhi-Xiang],
Yu, X.[Xuchu],
Sun, Y.F.[Yi-Fan],
Gao, K.L.[Kui-Liang],
Hyperspectral image classification with deep 3D capsule network and
Markov random field,
IET-IPR(16), No. 1, 2022, pp. 79-91.
DOI Link
2112
BibRef
Cao, Y.[Yi],
Ji, H.B.[Hong-Bing],
Zhang, W.[Wenbo],
Shirani, S.[Shahram],
Feature Aggregation Networks Based on Dual Attention Capsules for
Visual Object Tracking,
CirSysVideo(32), No. 2, February 2022, pp. 674-689.
IEEE DOI
2202
Feature extraction, Neurons, Visualization, Object tracking,
Computational modeling, Interference, Benchmark testing,
penalty attention
BibRef
Shi, R.Y.[Rui-Yang],
Niu, L.F.[Ling-Feng],
Zhou, R.Z.[Rui-Zhi],
Sparse CapsNet with explicit regularizer,
PR(124), 2022, pp. 108486.
Elsevier DOI
2203
Capsule network, Model compression, Sparse regularization,
Proximal gradient descent
BibRef
Lei, R.M.[Run-Min],
Zhang, C.J.[Chun-Ju],
Zhang, X.Y.[Xue-Ying],
Huang, J.W.[Jian-Wei],
Li, Z.X.[Zhen-Xuan],
Liu, W.C.[Wen-Cong],
Cui, H.[Hao],
Multiscale Feature Aggregation Capsule Neural Network for
Hyperspectral Remote Sensing Image Classification,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Tao, J.W.[Jian-Wei],
Zhang, X.K.[Xian-Kun],
Luo, X.X.[Xue-Xiong],
Wang, Y.[Yuan],
Song, C.[Chen],
Sun, Y.[Yue],
Adaptive Capsule Network,
CVIU(218), 2022, pp. 103405.
Elsevier DOI
2205
Capsule network, Adaptive value, Primary capsule layer,
Spatial relationship, Convolutional neural networks
BibRef
Chen, Y.S.[Yao-Sen],
Guo, B.[Bing],
Shen, Y.[Yan],
Wang, W.[Wei],
Lu, W.C.[Wei-Chen],
Suo, X.H.[Xin-Hua],
Capsule Boundary Network With 3D Convolutional Dynamic Routing for
Temporal Action Detection,
CirSysVideo(32), No. 5, May 2022, pp. 2962-2975.
IEEE DOI
2205
Proposals, Feature extraction, Routing,
Task analysis, Heuristic algorithms, Tensors, video features
BibRef
Ren, H.[Hao],
Lu, H.[Hong],
Compositional coding capsule network with k-means routing for text
classification,
PRL(160), 2022, pp. 1-8.
Elsevier DOI
2208
Text classification, Capsule network, Compositional code, Deep learning
BibRef
Zhou, Q.Q.[Qin-Qin],
Zheng, X.[Xiawu],
Cao, L.J.[Liu-Juan],
Zhong, B.N.[Bi-Neng],
Xi, T.[Teng],
Zhang, G.[Gang],
Ding, E.[Errui],
Xu, M.L.[Ming-Liang],
Ji, R.R.[Rong-Rong],
EC-DARTS: Inducing Equalized and Consistent Optimization into DARTS,
ICCV21(11966-11975)
IEEE DOI
2203
Bridges, Correlation, Graphics processing units, Transforms,
Optimization, Machine learning architectures and formulations, Explainable AI
BibRef
Sato, T.[Takumi],
Hotta, K.[Kazuhiro],
CNN to Capsule Network Transformation,
DICTA20(1-2)
IEEE DOI
2201
Image segmentation, Microprocessors, Transfer learning, Stacking,
Semantics, Network architecture, Task analysis, Capsule Network,
cell segmentation
BibRef
Jeong, M.[Minki],
Kim, C.[Changick],
A Parameter Efficient Multi-Scale Capsule Network,
ICIP21(739-743)
IEEE DOI
2201
Training, Image processing, Capsule network, Parameter reduction, Multi-scale
BibRef
Rezwan, I.M.[Ifty Mohammad],
Ahmed, M.B.[Mirza Belal],
Sourav, S.S.[Shazzad Sakim],
Quader, E.[Ezab],
Hossain, A.[Arafat],
Mohammed, N.[Nabeel],
MixCaps: Capsules With Iteration Free Routing,
DICTA20(1-8)
IEEE DOI
2201
Computational modeling, Digital images, Memory management, Routing,
Feature extraction, capsule neural networks, routing
BibRef
Pucci, R.[Rita],
Micheloni, C.[Christian],
Martinel, N.[Niki],
Self-Attention Agreement Among Capsules,
DSC21(272-280)
IEEE DOI
2112
Training, Head, Computer architecture,
Benchmark testing, Routing, Data models
BibRef
Gu, J.D.[Jin-Dong],
Tresp, V.[Volker],
Hu, H.[Han],
Capsule Network is Not More Robust than Convolutional Network,
CVPR21(14304-14312)
IEEE DOI
2111
Aggregates, Semantics, Routing, Robustness,
Pattern recognition, Task analysis
BibRef
Ma, D.[Ding],
Wu, X.Q.[Xiang-Qian],
CapsuleRRT: Relationships-aware Regression Tracking via Capsules,
CVPR21(10943-10952)
IEEE DOI
2111
Target tracking, Meetings, Routing,
Pattern recognition, Task analysis, Image classification
BibRef
Pucci, R.[Rita],
Micheloni, C.[Christian],
Foresti, G.L.[Gian Luca],
Martinel, N.[Niki],
Fixed simplex coordinates for angular margin loss in CapsNet,
ICPR21(3042-3049)
IEEE DOI
2105
Training, Analytical models, Image coding, Computational modeling,
Computer architecture, Predictive models, Benchmark testing, image analysis
BibRef
Wu, F.Y.[Fang-Yu],
Smith, J.S.[Jeremy S.],
Lu, W.J.[Wen-Jin],
Zhang, B.L.[Bai-Ling],
Pose-robust Face Recognition by Deep Meta Capsule network-based
Equivariant Embedding,
ICPR21(8695-8702)
IEEE DOI
2105
Databases, Face recognition, Aerospace electronics, Feature extraction
BibRef
Özcan, B.[Baris],
Kinli, F.[Furkan],
Kiraç, F.[Furkan],
Quaternion Capsule Networks,
ICPR21(6858-6865)
IEEE DOI
2105
Visualization, Quaternions, Neurons, Benchmark testing, Tools,
Computational efficiency, Pattern recognition
BibRef
RaviPrakash, H.[Harish],
Anwar, S.M.[Syed Muhammad],
Bagci, U.[Ulas],
Variational Capsule Encoder,
ICPR21(5820-5827)
IEEE DOI
2105
Pattern recognition, Bayes methods, Task analysis,
Image reconstruction, Standards, VAE, capsule network,
deep learning
BibRef
Jung, D.[Dahuin],
Lee, J.H.[Jong-Hyun],
Yi, J.[Jihun],
Yoon, S.R.[Sung-Roh],
iCaps: An Interpretable Classifier via Disentangled Capsule Networks,
ECCV20(XIX:314-330).
Springer DOI
2011
BibRef
Wu, F.Y.[Fang-Yu],
Smith, J.S.[Jeremy S.],
Lu, W.J.[Wen-Jin],
Pang, C.Y.[Chao-Yi],
Zhang, B.L.[Bai-Ling],
Attentive Prototype Few-shot Learning with Capsule Network-based
Embedding,
ECCV20(XXVIII:237-253).
Springer DOI
2011
BibRef
Gu, J.,
Tresp, V.,
Improving the Robustness of Capsule Networks to Image Affine
Transformations,
CVPR20(7283-7291)
IEEE DOI
2008
Routing, Couplings, Robustness, Visualization, Training,
Heuristic algorithms, Backpropagation
BibRef
Piciarelli, C.[Claudio],
Mishra, P.[Pankaj],
Foresti, G.L.[Gian Luca],
Image Anomaly Detection with Capsule Networks and Imbalanced Datasets,
CIAP19(I:257-267).
Springer DOI
1909
BibRef
Phong, N.H.[Nguyen Huu],
Ribeiro, B.[Bernardete],
An Improvement for Capsule Networks Using Depthwise Separable
Convolution,
IbPRIA19(I:521-530).
Springer DOI
1910
image background can challenge its performance.
BibRef
Zhao, L.,
Huang, L.,
Exploring Dynamic Routing As A Pooling Layer,
SDL-CV19(738-742)
IEEE DOI
2004
convolutional neural nets, pooling layer,
routing-by-agreement mechanism, capsule network,
interpretability
BibRef
Rajasegaran, J.[Jathushan],
Jayasundara, V.[Vinoj],
Jayasekara, S.[Sandaru],
Jayasekara, H.[Hirunima],
Seneviratne, S.[Suranga],
Rodrigo, R.[Ranga],
DeepCaps: Going Deeper With Capsule Networks,
CVPR19(10717-10725).
IEEE DOI
2002
BibRef
Ferrarini, B.[Bruno],
Ehsan, S.[Shoaib],
Bartoli, A.[Adrien],
Leonardis, A.[Ale],
McDonald-Maier, K.D.[Klaus D.],
Assessing Capsule Networks with Biased Data,
SCIA19(90-100).
Springer DOI
1906
Capsule networks introduced to deal with biased data.
BibRef
Phaye, S.S.R.[Sai Samarth R.],
Sikka, A.[Apoorva],
Dhall, A.[Abhinav],
Bathula, D.R.[Deepti R.],
Multi-level Dense Capsule Networks,
ACCV18(V:577-592).
Springer DOI
1906
BibRef
Ramasinghe, S.[Sameera],
Athuraliya, C.D.,
Khan, S.H.[Salman H.],
A Context-Aware Capsule Network for Multi-label Classification,
BrainDriven18(III:546-554).
Springer DOI
1905
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Recurrent Neural Networks for Shapes and Complex Features, RNN .