A light and faster regional convolutional neural network for object detection in optical remote sensing images
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Ding et al. (2018) enhanced the structure of the base VGG16-Net algorithm for improving the precision of airplane and car detection.
“Ding et al. (2018) enhanced the structure of the base VGG16-Net algorithm for improving the precision of airplane and car detection”
From Deep learning in remote sensing applications: A meta-analysis and review (2019) · cites this paper as Ding et al. (2018)
Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474 · see citing works
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946 · see citing works
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126 · see citing works
Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 74,248 · see citing works
Gradient-based learning applied to document recognition
Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805 · see citing works
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 56,035 · see citing works
You Only Look Once: Unified, Real-Time Object Detection
Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803 · see citing works
Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298594 · Cited by 48,562 · see citing works
(2014) · Cited by 33,419 · see citing works
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684 · see citing works
(2016) · Cited by 31,590 · see citing works
Girshick, R. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.169 · Cited by 28,105 · see citing works
SSD: Single Shot MultiBox Detector
Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., & Berg, A. C. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46448-0_2 · Cited by 22,128 · see citing works
YOLO9000: Better, Faster, Stronger
Redmon, J., & Farhadi, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.690 · Cited by 19,892 · see citing works
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
He, K., Zhang, X., Ren, S., & Sun, J. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.123 · Cited by 19,741 · see citing works
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570 · see citing works
Visualizing and understanding convolutional networks
Zeiler, M. D., & Fergus, R. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10590-1_53 · Cited by 15,839 · see citing works
(2010) · Cited by 14,134 · see citing works
Aggregated Residual Transformations for Deep Neural Networks
Xie, S., Girshick, R., Dollar, P., Tu, Z., & He, K. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.634 · Cited by 12,465 · see citing works
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2389824 · Cited by 11,971 · see citing works
Caffe: Convolutional Architecture for Fast Feature Embedding
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. (2014) · Proceedings of the 22nd ACM international conference on Multimedia · doi:10.1145/2647868.2654889 · Cited by 11,077 · see citing works
(2010) · Cited by 8,261 · see citing works
ADADELTA: An Adaptive Learning Rate Method
Zeiler, M. D. (2012) · arXiv · doi:10.48550/arxiv.1212.5701 · Cited by 5,322 · see citing works
R-FCN: Object Detection via Region-based Fully Convolutional NetworksPreprint
Dai, J., Li, Y., He, K., & Sun, J. Z. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.06409 · Cited by 5,135 · see citing works
Training Region-Based Object Detectors with Online Hard Example Mining
Shrivastava, A., Gupta, A., & Girshick, R. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.89 · Cited by 2,686 · see citing works
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., & LeCun, Y. (2013) · arXiv · doi:10.48550/arxiv.1312.6229 · Cited by 2,680 · see citing works
Edge Boxes: Locating Object Proposals from Edges
Zitnick, C. L., & Dollár, P. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_26 · Cited by 2,656 · see citing works
Deep learning for visual understanding: A review
Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., & Lew, M. S. (2016) · Neurocomputing · doi:10.1016/j.neucom.2015.09.116 · Cited by 2,504 · see citing works
On the momentum term in gradient descent learning algorithms
Ning Qian, A. (1999) · Neural Networks · doi:10.1016/s0893-6080(98)00116-6 · Cited by 2,318 · see citing works
Neural Networks: Tricks of the Trade: Second Edition
(2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-35289-8 · Cited by 2,116 · see citing works
Stochastic Gradient Descent Tricks
Bottou, L. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-35289-8_25 · Cited by 2,097 · see citing works
Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition
Scherer, D., Müller, A., & Behnke, S. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15825-4_10 · Cited by 1,556 · see citing works
A survey on object detection in optical remote sensing images
Cheng, G., & Han, J. (2016) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2016.03.014 · Cited by 1,503 · see citing works
Large-Margin Softmax Loss for Convolutional Neural NetworksPreprint
Liu, W., Wen, Y., Yu, Z., & Yang, M. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1612.02295 · Cited by 1,287 · see citing works
Big data deep learning: Challenges and perspectives
Chen, X.-W., & Lin, X. (2014) · IEEE Access · doi:10.1109/access.2014.2325029 · Cited by 1,255 · see citing works
HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection
Kong, T., Yao, A., Chen, Y., & Sun, F. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.98 · Cited by 934 · see citing works
A new deep convolutional neural network for fast hyperspectral image classification
Paoletti, M. E., Haut, J. M., Plaza, J., & Plaza, A. (2017) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2017.11.021 · Cited by 606 · see citing works
Orientation robust object detection in aerial images using deep convolutional neural network
Zhu, H., Chen, X., Dai, W., Fu, K., Ye, Q., & Jiao, J. (2015) · 2015 IEEE International Conference on Image Processing (ICIP) · doi:10.1109/icip.2015.7351502 · Cited by 483 · see citing works
Alshehhi, R., Marpu, P., Woon, W. L., & Mura, M. D. (2017) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2017.05.002 · Cited by 408 · see citing works
A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification
Zhang, C., Pan, X., Li, H., Gardiner, A., Sargent, I., Hare, J. S., & Atkinson, P. (2017) · Isprs Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2017.07.014 · Cited by 396 · see citing works
Deep Learning Approach for Car Detection in UAV Imagery
Ammour, N., Alhichri, H. S., Bazi, Y., Benjdira, B., Alajlan, N., & Zuair, M. (2017) · Remote Sensing · doi:10.3390/rs9040312 · Cited by 296 · see citing works
Tang, T., Zhou, S., Deng, Z., Zou, H., & Lei, L. (2017) · Sensors · doi:10.3390/s17020336 · Cited by 282 · see citing works
Weakly Supervised Learning Based on Coupled Convolutional Neural Networks for Aircraft Detection
Zhang, F., Du, B., Zhang, L., & Xu, M. (2016) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2016.2569141 · Cited by 257 · see citing works
Recurrently Target-Attending Tracking
Cui, Z., Xiao, S., Feng, J., & Yan, S. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.161 · Cited by 153 · see citing works
Fast aircraft detection in satellite images based on convolutional neural networks
Wu, H., Zhang, H., Zhang, J., & Xu, F. (2015) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2015.7351599 · Cited by 81 · see citing works
Cao, Y., Niu, X., & Dou, Y. (2016) · International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) · doi:10.1109/fskd.2016.7603232 · Cited by 52 · see citing works
Expressiveness of Rectifier NetworksPreprint
Pan, X., & Srikumar, V. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.05678 · Cited by 35 · see citing works
Fytsilis, A., Prokos, A., Koutroumbas, K., Michail, D., & Kontoes, C. (2016) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2016.06.001 · Cited by 28 · see citing works
Salakhutdinov, R. (2014) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2623330.2630809 · Cited by 26 · see citing works
Kabani, A., & El-Sakka, M. R. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-41501-7_41 · Cited by 24 · see citing works
Convolutional Neural Network with Biologically Inspired ON/OFF ReLU
Kim, J., Kim, S., & Lee, M. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-26561-2_38 · Cited by 9 · see citing works
LS-SVM application for ship course model predictive control
Jiang, S., Jin, H., & Wei, F. (2013) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma.2013.6618156 · Cited by 7 · see citing works
Product Schemes Evaluation Method Based on Improved BP Neural Network
Chen, W., Wei, X., & Zhao, T. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85984-0_13 · Cited by 6 · see citing works
Flagged first, then by citations
2 of the 55 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Deep learning in remote sensing applications: A meta-analysis and review
Ma, L., Liu, Y., Zhang, X., Ye, Y., Yin, G., & Johnson, B. A. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.04.015 · Cited by 2,456 · see citing works
Sun, A. Y., & Scanlon, B. R. (2019) · Environmental Research Letters · doi:10.1088/1748-9326/ab1b7d · Cited by 556 · see citing works
AlMansour, N., Syed, H. F., Khayat, N. R., Al-Theeb, R., Juri, R. E., Alhiyafi, J. A., Alrashed, S., & Olatunji, S. O. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.04.017 · Cited by 307 · see citing works
Computer vision applications in construction safety assurance
Fang, W., Ding, L., Love, P. E. D., Luo, H., Li, H., Pena-Mora, F. A., Zhong, B., & Zhou, C. (2019) · Automation in Construction · doi:10.1016/j.autcon.2019.103013 · Cited by 290 · see citing works
Yan, X., Tinghua Ai, A., Yang, M. J., & Yin, H. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.02.010 · Cited by 269 · see citing works
Li, W., He, C., Fang, J., Zheng, J., Fu, H., & Yu, L. (2019) · Remote Sensing · doi:10.3390/rs11040403 · Cited by 246 · see citing works
Skin Lesion Analyser: An Efficient Seven-Way Multi-class Skin Cancer Classification Using MobileNet
Chaturvedi, S. S., Gupta, K., & Prasad, P. S. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-981-15-3383-9_15 · Cited by 222 · see citing works
Deep Learning-Based Object Detection Techniques for Remote Sensing Images: A Survey
Li, Z., Wang, Y., Zhang, N., Zhang, Y., Zhao, Z., Xu, D., Ben, G., & Gao, Y. (2022) · Remote Sensing · doi:10.3390/rs14102385 · Cited by 219 · see citing works
Self-citationHao, Z., Lin, L., Post, C. J., Mikhailova, E. A., Li, M., Chen, Y., Yu, K., & Liu, J. (2021) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2021.06.003 · Cited by 205 · see citing works
Zhang, X., Han, L., Han, L., & Zhu, L. (2020) · Remote Sensing · doi:10.3390/rs12030417 · Cited by 187 · see citing works
Remote Sensing Object Detection Meets Deep Learning: A metareview of challenges and advances
Zhang, X., Zhang, T., Wang, G., Zhu, P., Tang, X., Jia, X., & Jiao, L. (2023) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2023.3312347 · Cited by 191 · see citing works
Hoeser, T., Bachofer, F., & Kuenzer, C. (2020) · Remote Sensing · doi:10.3390/rs12183053 · Cited by 181 · see citing works
YOLO-Fine: One-Stage Detector of Small Objects Under Various Backgrounds in Remote Sensing Images
Pham, M., Courtrai, L., Friguet, C., Lefèvre, S., & Baussard, A. (2020) · Remote Sensing · doi:10.3390/rs12152501 · Cited by 175 · see citing works
Li, W., Dong, R., Fu, H., & Yu, L. (2018) · Remote Sensing · doi:10.3390/rs11010011 · Cited by 164 · see citing works
Li, Y., Zhang, Y., Huang, X., & Yuille, A. (2018) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2018.09.014 · Cited by 144 · see citing works
Self-citationFeature Split–Merge–Enhancement Network for Remote Sensing Object Detection
Ma, W., Li, N., Zhu, H., Jiao, L., Tang, X., Guo, Y., & Hou, B. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3140856 · Cited by 140 · see citing works
A New Spatial-Oriented Object Detection Framework for Remote Sensing Images
Yu, D., & Ji, S. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3127232 · Cited by 136 · see citing works
Zhang, W., Witharana, C., Liljedahl, A., & Kanevskiy, M. (2018) · Remote Sensing · doi:10.3390/rs10091487 · Cited by 129 · see citing works
Smallholder Crop Area Mapped with a Semantic Segmentation Deep Learning Method
Du, Z., Yang, J., Ou, C., & Zhang, T. (2019) · Remote Sensing · doi:10.3390/rs11070888 · Cited by 114 · see citing works
Light-YOLOv4: An Edge-Device Oriented Target Detection Method for Remote Sensing Images
Ma, X., Ji, K., Xiong, B., Zhang, L., Feng, S., & Kuang, G. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3120009 · Cited by 107 · see citing works
Arbitrary-Oriented Object Detection in Remote Sensing Images Based on Polar Coordinates
Zhou, L., Wei, H., Li, H., Zhao, W., Zhang, Y., & Zhang, Y. (2020) · IEEE Access · doi:10.1109/access.2020.3041025 · Cited by 133 · see citing works
Self-citationCombining deep learning and ontology reasoning for remote sensing image semantic segmentation
Li, Y., Ouyang, S., & Zhang, Y. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.108469 · Cited by 95 · see citing works
Self-citationShivappriya, S. N., Priyadarsini, M. J. P., Stateczny, A., Puttamadappa, C., & Parameshachari, B. D. (2021) · Remote Sensing · doi:10.3390/rs13020200 · Cited by 94 · see citing works
Zheng, Z., Zhong, Y., Ma, A., Han, X., Zhao, J. J., Liu, Y., & Zhang, L. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2020.04.019 · Cited by 91 · see citing works
YOLO-HR: Improved YOLOv5 for Object Detection in High-Resolution Optical Remote Sensing Images
Wan, D., Lu, R., Wang, S., Shen, S., Xu, T., & Lang, X. (2023) · Remote Sensing · doi:10.3390/rs15030614 · Cited by 90 · see citing works
Pearse, G. D., Tan, Y. S., Watt, M. S., Franz, M., & Dash, J. P. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2020.08.005 · Cited by 88 · see citing works
Convolutional neural network approach for automatic tympanic membrane detection and classification
Başaran, E., Cömert, Z., & Çelik, Y. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.101734 · Cited by 86 · see citing works
LO-Det: Lightweight Oriented Object Detection in Remote Sensing Images
Huang, Z., Li, W., Xia, X., Wang, H., Jie, F., & Tao, R. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3067470 · Cited by 86 · see citing works
Zhang, T., Zhuang, Y., Wang, G., Dong, S., Chen, H., & Li, L. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3108476 · Cited by 84 · see citing works
Geographical Knowledge-Driven Representation Learning for Remote Sensing Images
Li, W., Chen, K., Chen, H., & Shi, Z. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3115569 · Cited by 86 · see citing works
Ajayi, O. G., & Ashi, J. (2022) · Smart Agricultural Technology · doi:10.1016/j.atech.2022.100128 · Cited by 81 · see citing works
AI-based object detection latest trends in remote sensing, multimedia and agriculture applications
Nawaz, S., Li, J.-B., Bhatti, U., Shoukat, M., & Ahmad, R. M. (2022) · Frontiers in Plant Science · doi:10.3389/fpls.2022.1041514 · Cited by 67 · see citing works
A2RMNet: Adaptively Aspect Ratio Multi-Scale Network for Object Detection in Remote Sensing Images
Qiu, H., Li, H., Wu, Q., Meng, F., Ngan, K. N., & Shi, H. (2019) · Remote Sensing · doi:10.3390/rs11131594 · Cited by 77 · see citing works
Deep learning-based automatic detection of productive tillers in rice
Deng, R., Jiang, Y., Tao, M., Huang, X., Bangura, K., Liu, C., Lin, J., & Qi, L. (2020) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2020.105703 · Cited by 72 · see citing works
A systematic review of object detection from images using deep learning
Kaur, J., & Singh, W. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15981-y · Cited by 75 · see citing works
Aircraft detection in remote sensing image based on corner clustering and deep learning
Liu, Q., Xiang, X., Wang, Y., Luo, Z., & Fang, F. (2019) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2019.103333 · Cited by 70 · see citing works
Moving Vehicle Detection for Remote Sensing Video Surveillance with Nonstationary Satellite Platform
Zhang, J., Jia, X., Hu, J., & Tan, K. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3066696 · Cited by 70 · see citing works
Saeedimoghaddam, M., & Stepinski, T. F. (2019) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2019.1696968 · Cited by 69 · see citing works
Verschoof, W. B., Lambers, K., Kowalczyk, W., & Bourgeois, Q. P. J. (2020) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi9050293 · Cited by 67 · see citing works
Ge, S., Zhang, J., Pan, Y., Yang, Z., & Zhu, S. (2021) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2021.102451 · Cited by 64 · see citing works
X-LineNet: Detecting Aircraft in Remote Sensing Images by a Pair of Intersecting Line Segments
Wei, H., Zhang, Y., Wang, B., Yang, Y., Li, H., & Wang, H. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.2999082 · Cited by 63 · see citing works
Self-citationOlatunji, S. O., Alotaibi, S., Almutairi, E., Alrabae, Z., Almajid, Y., Altabee, R., Altassan, M., Ahmed, M. I. B., Farooqui, M., & Alhiyafi, J. A. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104267 · Cited by 63 · see citing works
Learning to Classify Structures in ALS-Derived Visualizations of Ancient Maya Settlements with CNN
Somrak, M., Džeroski, S., & Kokalj, Ž. (2020) · Remote Sensing · doi:10.3390/rs12142215 · Cited by 59 · see citing works
Vehicle Detection From High-Resolution Remote Sensing Imagery Using Convolutional Capsule Networks
Yu, Y., Gu, T., Guan, H., Li, D., & Jin, S. (2019) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2019.2912582 · Cited by 56 · see citing works
Coupling of deep learning and remote sensing: a comprehensive systematic literature review
Yasir, M., Jianhua, W., Liu, S., Sheng, H., Xu, M., & Hossain, M. S. (2023) · International Journal of Remote Sensing · doi:10.1080/01431161.2022.2161856 · Cited by 50 · see citing works
Du, L., McCarty, G. W., Zhang, X., Lang, M., Vanderhoof, M. K., Li, X., Huang, C., Lee, S., & Zou, Z. (2020) · Remote Sensing · doi:10.3390/rs12040644 · Cited by 50 · see citing works
A fast self-attention cascaded network for object detection in large scene remote sensing images
Hua, X., Wang, X., Rui, T., Zhang, H., & Wang, D. (2020) · Applied Soft Computing · doi:10.1016/j.asoc.2020.106495 · Cited by 48 · see citing works
A Contextual Bidirectional Enhancement Method for Remote Sensing Image Object Detection
Zhang, J., Xie, C., Xu, X., Shi, Z., & Pan, B. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3015049 · Cited by 48 · see citing works
Xue, F., Jin, W., Qiu, S., & Yang, J. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3128989 · Cited by 46 · see citing works
Aircraft detection in satellite imagery using deep learning-based object detectors
Azam, B., Khan, M. J., Bhatti, F., Maud, A. R., Hussain, S. F., Hashmi, A., & Khurshid, K. (2022) · Microprocessors and microsystems · doi:10.1016/j.micpro.2022.104630 · Cited by 38 · see citing works
Farmland Parcel Mapping in Mountain Areas Using Time-Series SAR Data and VHR Optical Images
Liu, W., Wang, J., Luo, J., Wu, Z., Chen, J., Zhou, Y., Sun, Y., Shen, Z., Xu, N., & Yang, Y. (2020) · Remote Sensing · doi:10.3390/rs12223733 · Cited by 44 · see citing works
Song, G., Wu, S., Lee, C. K. F., Serbin, S. P., Wolfe, B. T., Ng, M. K., Ely, K., Bogonovich, M., Wang, J., Lin, Z., et al. (2021) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2021.10.023 · Cited by 43 · see citing works
MM-RCNN: Toward Few-Shot Object Detection in Remote Sensing Images With Meta Memory
Li, J., Tian, Y. W., Xu, Y., Hu, X., Zhang, Z., Hu, W., & Xiao, Y. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3228612 · Cited by 41 · see citing works
On-orbit monitoring flying aircraft day and night based on SDGSAT-1 thermal infrared dataset
Li, L., Zhou, X., Hu, Z., Gao, L., Li, X., Ni, X., & Chen, F. (2023) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113840 · Cited by 41 · see citing works
An Approach on Image Processing of Deep Learning Based on Improved SSD
Jin, L., & Liu, G. (2021) · Symmetry · doi:10.3390/sym13030495 · Cited by 42 · see citing works
Online Structured Sparsity-Based Moving-Object Detection From Satellite Videos
Zhang, J., Jia, X., Hu, J., & Chanussot, J. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.2976855 · Cited by 40 · see citing works
CRPN-SFNet: A High-Performance Object Detector on Large-Scale Remote Sensing Images
Lin, Q., Zhao, J., Fu, G., & Yuan, Z. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3027924 · Cited by 40 · see citing works
Tree-based convolutional neural networks for object classification in segmented satellite images
Robinson, H., Vimal, S., Khari, M., López, F., & Crespo, R. A. G. (2020) · The International Journal of High Performance Computing Applications · doi:10.1177/1094342020945026 · Cited by 39 · see citing works
Vision-Based Activity Classification of Excavators by Bidirectional LSTM
Kim, I.-S., Latif, K., Kim, J., Sharafat, A., Lee, D., & Seo, J. (2022) · Applied Sciences · doi:10.3390/app13010272 · Cited by 37 · see citing works
Zhu, D., Xia, S., Zhao, J., Zhou, Y. Z., Jian, M., Niu, Q., Yao, R., & Chen, Y. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.10.065 · Cited by 37 · see citing works
Orientation guided anchoring for geospatial object detection from remote sensing imagery
Yu, Y., Guan, H., Li, D., Gu, T., Tang, E., & Li, A. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.12.001 · Cited by 36 · see citing works
Zhu, Z., Wang, P., Diao, W., Yang, J., Wang, H., & Sun, X. (2023) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2022.12.024 · Cited by 33 · see citing works
Cira, C.-I., Alcarria, R., Manso-Callejo, M.-Á., & Serradilla, F. (2020) · Remote Sensing · doi:10.3390/rs12050765 · Cited by 20 · see citing works
A Hierarchical Airport Detection Method Using Spatial Analysis and Deep Learning
Zeng, F., Cheng, L., Li, N., Xia, N., Ma, L., Zhou, X., & Li, M. (2019) · Remote Sensing · doi:10.3390/rs11192204 · Cited by 31 · see citing works
Objects detection for remote sensing images based on polar coordinatesPreprint
Zhou, L., Wei, H., Li, H., Zhao, W., Zhang, Y., & Zhang, Y. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.02988 · Cited by 31 · see citing works
Self-citationℱ3-Net: Feature Fusion and Filtration Network for Object Detection in Optical Remote Sensing Images
Ye, X., Xiong, F., Lu, J., Zhou, J. W., & Qian, Y. (2020) · Remote Sensing · doi:10.3390/rs12244027 · Cited by 29 · see citing works
Double Head Predictor based Few-Shot Object Detection for Aerial Imagery
Wolf, S., Meier, J., Sommer, L. W., & Beyerer, J. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00086 · Cited by 29 · see citing works
Instance Segmentation in Remote Sensing Imagery using Deep Convolutional Neural Networks
Potlapally, A., Chowdary, P. S. R., Shekhar, S. S. R., Mishra, N., Madhuri, C. S. V. D., & Prasad, A. V. V. (2019) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i46837.2019.9055569 · Cited by 28 · see citing works
Wu, Z., Xu, J., Wang, Y., Sun, F., Tan, M., & Weise, T. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.10.010 · Cited by 28 · see citing works
Complex Optical Remote-Sensing Aircraft Detection Dataset and Benchmark
Shi, T., Gong, J., Jiang, S., Zhi, X., Bao, G., Sun, Y., & Zhāng, W. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3283137 · Cited by 28 · see citing works
Small Manhole Cover Detection in Remote Sensing Imagery with Deep Convolutional Neural Networks
Liu, W., Cheng, D., Yin, P., Yang, M., Li, E., Xie, M., & Zhang, L. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8010049 · Cited by 27 · see citing works
Tang, Z., Wang, H., Li, X., Li, X., Cai, W., & Han, C. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.2983439 · Cited by 27 · see citing works
Li, B., Gao, J., Chen, S., Lim, S., & Jiang, H. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3174399 · Cited by 24 · see citing works
Potential of eye-tracking for interactive geovisual exploration aided by machine learning
Keskin, M., & Kettunen, P. (2023) · International Journal of Cartography · doi:10.1080/23729333.2022.2150379 · Cited by 24 · see citing works
Pang, Y., Zhang, Y., Kong, Q., Wang, Y., Chen, B., & Cao, X. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3269642 · Cited by 24 · see citing works
Self-citationTabata, A. N., Zimmer, A., Coelho, L. D. S., & Mariani, V. C. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120200 · Cited by 24 · see citing works
A Novel Effectively Optimized One-Stage Network for Object Detection in Remote Sensing Imagery
Xie, W., Qin, H., Li, Y., Wang, Z., & Lei, J. (2019) · Remote Sensing · doi:10.3390/rs11111376 · Cited by 23 · see citing works
Tien, P. W., Wei, S., Calautit, J. K., Darkwa, J., & Wood, C. J. (2020) · Journal of Sustainable Development of Energy Water and Environment Systems · doi:10.13044/j.sdewes.d8.0378 · Cited by 22 · see citing works
Mo, N., Li, Y., Zhu, R., & Xie, H. T. (2019) · Remote Sensing · doi:10.3390/rs11030272 · Cited by 22 · see citing works
Ship Detection for Optical Remote Sensing Images Based on Visual Attention Enhanced Network
Bi, F., Hou, J., Chen, L., Yang, Z., & Wang, Y. (2019) · Sensors · doi:10.3390/s19102271 · Cited by 23 · see citing works
Development and evolution of YOLO in object detection: A survey
Tian, Y., Xu, W., Yang, B., Yang, X., Guo, H., Wang, G., & Yu, H. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132436 · Cited by 27 · see citing works
Lavanya, K., V, Karnick, S., Ghalib, M. R., Shankar, A., Khapre, S. P., & Tayubi, I. A. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12613-9 · Cited by 25 · see citing works
Liu, Y., Su, J., Shen, L., Lu, N., Fang, Y., Liu, F., Song, Y., & Su, B. (2021) · International journal of agricultural and biological engineering · doi:10.25165/j.ijabe.20211405.6593 · Cited by 23 · see citing works
Point Cloud Semantic Segmentation Network Based on Multi-Scale Feature Fusion
Du, J., Jiang, Z., Huang, S., Wang, Z., Su, J., Su, S., Wu, Y., & Cai, G. (2021) · Sensors · doi:10.3390/s21051625 · Cited by 21 · see citing works
Callejo, M. Á. M., Cira, C.-I., Alcarria, R., & Justel, J. J. A. (2020) · Remote Sensing · doi:10.3390/rs12223743 · Cited by 20 · see citing works
Jiao, S., Hu, D., Shen, Z., Wang, H., Dong, W., Guo, Y., Li, S., Lei, Y., Kou, W., Wang, J., et al. (2022) · Remote Sensing · doi:10.3390/rs14092015 · Cited by 19 · see citing works
A Specially Optimized One-Stage Network for Object Detection in Remote Sensing Images
Qin, H., Li, Y., Lei, J., Xie, W., & Wang, Z. (2020) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2020.2975086 · Cited by 17 · see citing works
Kouvaras, L., & Petropoulos, G. P. (2024) · Drones · doi:10.3390/drones8020043 · Cited by 17 · see citing works
Geographical Supervision Correction for Remote Sensing Representation Learning
Li, W., Chen, K., & Shi, Z. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3202499 · Cited by 16 · see citing works
Wu, Z., Li, H., Wang, Y., & Long, B. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.123233 · Cited by 16 · see citing works
TrCSVM: a novel approach for the classification of melanoma skin cancer using transfer learning
Singh, L., Janghel, R. R., & Sahu, S. P. (2020) · Data Technologies and Applications · doi:10.1108/dta-06-2020-0126 · Cited by 17 · see citing works
Callejo, M. Á. M., Cira, C.-I., Alcarria, R., & Matesanz, F. J. G. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3101934 · Cited by 16 · see citing works
Wenger, R., Puissant, A., Weber, J., Idoumghar, L., & Forestier, G. (2022) · International Journal of Remote Sensing · doi:10.1080/01431161.2022.2054295 · Cited by 15 · see citing works
A review on deep learning-based object tracking methods
Uke, N., Futane, P. R., Deshpande, N., & Uke, S. N. (2024) · Multiagent and Grid Systems · doi:10.3233/mgs-230126 · Cited by 15 · see citing works
Cao, S., Yu, Y., Guan, H., Peng, D., & Yan, W. (2019) · Remote Sensing · doi:10.3390/rs11141708 · Cited by 15 · see citing works
Appearance and Motion Based Persistent Multiple Object Tracking in Wide Area Motion Imagery
Sommer, L. W., Krüger, W. A., & Teutsch, M. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00434 · Cited by 14 · see citing works
Anchor-free object detection in remote sensing images using a variable receptive field network
Fu, S., He, Y., Du, X., & Zhu, Y. (2023) · EURASIP Journal on Advances in Signal Processing · doi:10.1186/s13634-023-01013-2 · Cited by 14 · see citing works
Bibliometric and visualized analysis of deep learning in remote sensing
Bai, Y., Sun, X.-Y., Ji, Y.-F., Huang, J.-H., Fu, W.-T., & Shi, H.-E. (2021) · International Journal of Remote Sensing · doi:10.1080/01431161.2021.1949069 · Cited by 13 · see citing works
FCC-Net: A Full-Coverage Collaborative Network for Weakly Supervised Remote Sensing Object Detection
Chen, S., Shao, D., Shu, X., Zhang, C., & Wang, J. (2020) · Electronics · doi:10.3390/electronics9091356 · Cited by 13 · see citing works
Multimodal Knowledge Distillation for Arbitrary-Oriented Object Detection in Aerial Images
Huang, Z., Li, W., & Tao, R. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10097119 · Cited by 13 · see citing works
- Authors
- Ding, P., Zhang, Y., Deng, W.-J., Jia, P., & Kuijper, A.
- Affiliations
- Chinese Academy of Sciences (CN)
- Fraunhofer Institute for Computer Graphics Research (DE)
- Corresponding author
- Ding, Peng
- Venue
- ISPRS Journal of Photogrammetry and Remote Sensing
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 141
- Pages
- 208-218
- ISSN
- 0924-2716 (ISSN-L)
- OpenAlex
- W2803867573
- Cited by
- 174
- References
- 55
- Citations by year
- 2026: 1 · 2025: 8 · 2024: 12 · 2023: 27 · 2022: 26 · 2021: 33 · 2020: 39 · 2019: 24 · 2018: 4
- FWCI
- 12.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ISPRS Journal of Photogrammetry and Remote Sensing (publishedVersion)
- Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (submittedVersion)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
- TUbilio (Technical University of Darmstadt) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Engineering › Media Technology › Remote-Sensing Image Classification
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Keywords
- object detection, optical remote sensing images, satellite imagery, Faster R-CNN, VGG16, dense convolutional network, multi-scale representation, memory reduction, aircraft detection, small object detection
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review