Machine learning
ResNeXt
ResNeXt은 Xie, Girshick, Dollár, Tu, He가 2017년 CVPR에서 소개한 심층 합성곱 신경망 아키텍처입니다.
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Method map
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출처
- Xie, S., Girshick, R., Dollár, P., Tu, Z., & He, K. (2017). Aggregated Residual Transformations for Deep Neural Networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5987–5995. DOI: 10.1109/CVPR.2017.634 ↗
- He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep Residual Learning for Image Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770–778. DOI: 10.1109/CVPR.2016.90 ↗
- Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. ISBN: 978-0-26-203561-3
이 페이지 인용 방법
ScholarGate. (2026, June 3). ResNeXt: Aggregated Residual Transformations for Deep Neural Networks. ScholarGate. https://scholargate.app/ko/deep-learning/resnext
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- DenseNet딥러닝↔ compare
- EfficientNet딥러닝↔ compare
- 모바일넷: 모바일 비전을 위한 효율적인 합성곱 신경망딥러닝↔ compare
- ResNet (Residual Network)딥러닝↔ compare