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cs.CV2022★ 1 cited
PENCIL: Deep Learning with Noisy Labels
Kun Yi, Guo-Hua Wang, Jianxin Wu
Deep learning has achieved excellent performance in various computer vision tasks, but requires a lot of training examples with clean labels. It is easy to collect a dataset with n…
cs.CV2022★ 3 cited
Training Vision Transformers with Only 2040 Images
Yun-Hao Cao, Hao Yu, Jianxin Wu
Vision Transformers (ViTs) is emerging as an alternative to convolutional neural networks (CNNs) for visual recognition. They achieve competitive results with CNNs but the lack of…