7.1.10.3 Small Objects, Detect Small Objects

Chapter Contents (Back)
Object Detection. Small Objects. See also ATR -- Small Targets IR, Infra-Red, Thermal, Applications.

Shirvaikar, M.V.[Mukul V.], and Trivedi, M.M.[Mohan M.],
A Neural Network Filter to Detect Small Targets in High-Clutter Backgrounds,
TNN(6), No. 1, January 1995, pp. 252-257. BibRef 9501

French, P.A., Zeidler, J.R., Ku, W.H.,
Enhanced Detectability of Small Objects in Correlated Clutter Using an Improved 2-D Adaptive Lattice Algorithm,
IP(6), No. 3, March 1997, pp. 383-397.
IEEE DOI 9703
< BibRef
Earlier:
An improved 2-D adaptive lattice filtering algorithm and its application to detection of small objects in correlated clutter,
ICIP94(I: 765-769).
IEEE DOI 9411
BibRef

Silva, D.M., Abdou, I.E., Warren, R.E.,
Optimum Detection of Small Targets in A Cluttered Background,
OptEng(37), No. 1, January 1998, pp. 83-92. 9802
BibRef

Chapple, P.B., Bertilone, D.C., Caprari, R.S., Newsam, G.N.,
Stochastic model-based processing for detection of small targets in non-gaussian natural imagery,
IP(10), No. 4, April 2001, pp. 554-564.
IEEE DOI 0104
BibRef

Segl, K.[Karl], Kaufmann, H.[Hermann],
Detection of small objects from high-resolution panchromatic satellite imagery based on supervised image segmentation,
GeoRS(39), No. 9, September 2001, pp. 2080-2083.
IEEE Top Reference. 0111
BibRef

Abe, D.[Daisuke], Segawa, E.[Eigo], Nakayama, O.[Osafumi], Shiohara, M.[Morito], Sasaki, S.[Shigeru], Sugano, N.[Nobuyuki], Kanno, H.[Hajime],
Robust Small-Object Detection for Outdoor Wide-Area Surveillance,
IEICE(E91-D), No. 7, July 2008, pp. 1922-1928.
DOI Link 0807
BibRef

Bai, X.Z.[Xiang-Zhi], Zhou, F.[Fugen],
Analysis of new top-hat transformation and the application for infrared dim small target detection,
PR(43), No. 6, June 2010, pp. 2145-2156.
Elsevier DOI 1003
Top-hat transformation; Structuring element; Infrared dim small target; Target detection BibRef

Zhang, M., Wu, T., Beeman, S.C., Cullen-McEwen, L., Bertram, J.F., Charlton, J.R., Baldelomar, E., Bennett, K.M.,
Efficient Small Blob Detection Based on Local Convexity, Intensity and Shape Information,
MedImg(35), No. 4, April 2016, pp. 1127-1137.
IEEE DOI 1604
biomedical MRI BibRef

Park, J.[Jinhee], Kwon, D.[Dokyeong], Choi, B.W.[Bo Won], Kim, G.Y.[Ga Young], Kim, K.Y.[Kwang Yong], Kwon, J.[Junseok],
Small object segmentation with fully convolutional network based on overlapping domain decomposition,
MVA(30), No. 4, June 2019, pp. 707-716.
Springer DOI 1906
BibRef

Shi, S., Liang, X., Shui, P., Zhang, J., Zhang, S.,
Low-Velocity Small Target Detection With Doppler-Guided Retrospective Filter in High-Resolution Radar at Fast Scan Mode,
GeoRS(57), No. 11, November 2019, pp. 8937-8953.
IEEE DOI 1911
Clutter, Sea surface, Market research, Radar clutter, Doppler effect, Radar detection, Doppler-guided retrospective filter (DGRF), structural trend BibRef

Guo, L.[Lie], Wang, D.X.[Dong-Xing], Li, L.H.[Lin-Hui], Feng, J.D.[Jin-Dun],
Accurate and fast single shot multibox detector,
IET-CV(14), No. 6, September 2020, pp. 391-398.
DOI Link 2010
Context enhancement. BibRef

Courtrai, L.[Luc], Pham, M.T.[Minh-Tan], Lefèvre, S.[Sébastien],
Small Object Detection in Remote Sensing Images Based on Super-Resolution with Auxiliary Generative Adversarial Networks,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef


Drid, K.[Khaoula], Allaoui, M.[Mebarka], Kherfi, M.L.[Mohammed Lamine],
Object Detector Combination for Increasing Accuracy and Detecting More Overlapping Objects,
ICISP20(290-296).
Springer DOI 2009
BibRef

Zhang, J.Y.[Jia-Yi], Liu, Y.[Ying], Liu, Z.Q.[Zhi-Qiang],
An Improved FAsT_Match Algorithm for Micro Parts Detection,
ICIVC20(24-28)
IEEE DOI 2009
Classification algorithms, Image segmentation, Shape, Image recognition, Approximation algorithms, Target tracking, micro assembly BibRef

Liu, Z., Gao, G., Sun, L., Fang, L.,
IPG-Net: Image Pyramid Guidance Network for Small Object Detection,
Anti-UAV20(4422-4430)
IEEE DOI 2008
Feature extraction, Object detection, Fuses, Semantics, Convolution, Task analysis, Streaming media BibRef

Chen, P., Hsieh, J., Wang, C., Liao, H.M.[H. Mark],
Recursive Hybrid Fusion Pyramid Network for Real-Time Small Object Detection on Embedded Devices,
LPCV20(1612-1621)
IEEE DOI 2008
Feature extraction, Object detection, Computational modeling, Iron, Detectors, Computational efficiency, Real-time systems BibRef

van Etten, A.[Adam],
Satellite Imagery Multiscale Rapid Detection with Windowed Networks,
WACV19(735-743)
IEEE DOI 1904
Small objects. application program interfaces, computer vision, geophysical image processing, geophysical techniques, BibRef

Yang, X., Yang, J., Yan, J., Zhang, Y., Zhang, T., Guo, Z., Sun, X., Fu, K.,
SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects,
ICCV19(8231-8240)
IEEE DOI 2004
Code, Object Detection.
WWW Link. feature extraction, image fusion, object detection, SCRDet, robust detection, natural images, Semantics BibRef

Liu, L., Muelly, M., Deng, J., Pfister, T., Li, L.,
Generative Modeling for Small-Data Object Detection,
ICCV19(6072-6080)
IEEE DOI 2004
learning (artificial intelligence), neural nets, object detection, machine learning, Generative adversarial networks BibRef

Razaak, M.[Manzoor], Kerdegari, H.[Hamideh], Argyriou, V.[Vasileios], Remagnino, P.[Paolo],
Multi-scale Feature Fused Single Shot Detector for Small Object Detection in UAV Images,
CVS19(778-786).
Springer DOI 1912
BibRef

Yang, Z.X.[Zi-Xuan], Chai, X.J.[Xiu-Juan], Wang, R.P.[Rui-Ping], Guo, W.J.[Wei-Jun], Wang, W.X.[Wei-Xuan], Pu, L.[Li], Chen, X.L.[Xi-Lin],
Prior Knowledge Guided Small Object Detection on High-Resolution Images,
ICIP19(86-90)
IEEE DOI 1910
small object detection, high-resolution image, prior knowledge, convolutional neural network BibRef

LaLonde, R., Zhang, D., Shah, M.,
ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information,
CVPR18(4003-4012)
IEEE DOI 1812
Object detection, Detectors, Computer vision, Feature extraction, Proposals, Search problems, Cameras BibRef

Wilms, C.[Christian], Frintrop, S.[Simone],
AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects,
ACCV18(II:678-694).
Springer DOI 1906
BibRef

Menikdiwela, M., Nguyen, C., Li, H., Shaw, M.,
CNN-based small object detection and visualization with feature activation mapping,
IVCNZ17(1-5)
IEEE DOI 1902
cellular neural nets, feature extraction, object detection, fined-tuned faster R-CNN, feature activation mapping, feature activation map BibRef

Zhou, X.Q., Zou, Y.X., Wang, Y.,
Accurate small object detection via density map aided saliency estimation,
ICIP17(425-429)
IEEE DOI 1803
Estimation, Image reconstruction, Image segmentation, Object detection, Task analysis, Training, superpixel BibRef

Mittal, S.[Sudhandhu], Karthik, M.S.[M. Siva], Kumar, S.[Suryansh], Krishna, K.M.[K. Madhava],
Small Object Discovery and Recognition Using Actively Guided Robot,
ICPR14(4334-4339)
IEEE DOI 1412
Accuracy BibRef

Razakarivony, S.[Sebastien], Jurie, F.[Frederic],
Discriminative Autoencoders for Small Targets Detection,
ICPR14(3528-3533)
IEEE DOI 1412
Manifolds BibRef

Lin, T.[Tao], Marot, J.[Julien], Bourennane, S.[Salah],
Small Target Detection Improvement in Hyperspectral Image,
ACIVS13(460-469).
Springer DOI 1311
BibRef

Samur, R., Zagorodnov, V.,
Segmenting Small Regions in the Presence of Noise,
ICIP05(II: 1254-1257).
IEEE DOI 0512
BibRef

Hinz, S.,
Fast and Subpixel Precise Blob Detection and Attribution,
ICIP05(III: 457-460).
IEEE DOI 0512
BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Maximally Stable Extremal Regions, MSER Descriptions .


Last update:Nov 23, 2020 at 10:27:11