The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Identity Mappings in Deep Residual Networks
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“By deepening the network and addressing the problem of a limited training dataset, the architecture of ResNet18 [30] improves the performance of visual categorization.”
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“Thus, the structure of ShuffleNet V2 realizes this type of feature re-use pattern by design . It shares the similar benefit of feature re-use for high accuracy as in DenseNet [6], but it is much more efficient as analyzed earlier.”
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“Second, in each block, half of feature channels (when c ′ = c/ 2) directly go through the block and join the next block. This can be regarded as a kind of feature reuse , in a similar spirit as in DenseNet [6] and CondenseNet [16].”
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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
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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
Self-citationBackpropagation Applied to Handwritten Zip Code Recognition
LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., & Jackel, L. D. (1989) · Neural Computation · doi:10.1162/neco.1989.1.4.541 · Cited by 11,891
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Szegedy, C., Ioffe, S., Vanhoucke, V., & Alemi, A. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v31i1.11231 · Cited by 4,636
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Cited by
Sorted by citations
Densely Connected Convolutional Networks
Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.243 · Cited by 48,566
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CBAM: Convolutional Block Attention Module
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Metadata
- Authors
- He, K., Zhang, X., Ren, S., & Sun, J.
- Affiliations
- Microsoft Research Asia (China) (CN)
- Corresponding author
- He, Kaiming
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 630-645
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2302255633
- Cited by
- 10,741
- References
- 6
- Citations by year
- 2026: 466 · 2025: 909 · 2024: 1286 · 2023: 1317 · 2022: 1365 · 2021: 1599 · 2020: 1446 · 2019: 1178 · 2018: 732 · 2017: 366 · 2016: 72
- FWCI
- 266.27
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Stochastic Gradient Optimization Techniques
- Keywords
- ResNet, identity mapping, skip connections, residual blocks, signal propagation, generalization, training stability
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