The DOI matches its Crossref record; 314 of the 314 references it cites were found in a registry or an index.
Deep neural network concepts for background subtraction:A systematic review and comparative evaluation
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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
Very Deep Convolutional Networks for Large-Scale Image Recognition
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ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404
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 73,472
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
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ImageNet: A large-scale hierarchical image database
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Cited by
A survey on deep learning and its applications
Dong, S., Wang, P., & Abbas, K. (2021) · Computer Science Review · doi:10.1016/j.cosrev.2021.100379 · Cited by 1,544
A Survey on Neural Network Interpretability
Zhang, Y., Tino, P., Leonardis, A., & Tang, K. (2021) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2021.3100641 · Cited by 923
Background subtraction in real applications: Challenges, current models and future directions
Garcia-Garcia, B., Bouwmans, T., & Rosales Silva, A. J. (2020) · Computer Science Review · doi:10.1016/j.cosrev.2019.100204 · Cited by 337
Self-citationKaveh, M., & Mesgari, M. S. (2023) · Neural Processing Letters · doi:10.1007/s11063-022-11055-6 · Cited by 292
Fish Detection and Classification for Automatic Sorting System with an Optimized YOLO Algorithm
Kuswantori, A., Suesut, T., Tangsrirat, W., Schleining, G., & Nunak, N. (2023) · Applied Sciences · doi:10.3390/app13063812 · Cited by 48
Metadata
- Authors
- Bouwmans, T., Javed, S., Sultana, M., & Jung, S. K.
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 117
- Pages
- 8-66
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2901951655
- Cited by
- 396
- References
- 314
- FWCI
- 11.03
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bouwmans, T., Javed, S., Sultana, M., & Jung, S. K. (2019). Deep neural network concepts for background subtraction:A systematic review and comparative evaluation. Neural Networks. https://doi.org/10.1016/j.neunet.2019.04.024
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