목록논문 리뷰 (37)

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[논문 리뷰] BYOL: Bootstrap Your Own Latent A New Approach to Self-Supervised Learning(2020)

이번에 리뷰할 논문은 Bootstrap Your Own LatentA New Approach to Self-Supervised Learning 입니다. https://paperswithcode.com/paper/bootstrap-your-own-latent-a-new-approach-to Papers with Code - Bootstrap your own latent: A new approach to self-supervised Learning #2 best model for Self-Supervised Person Re-Identification on SYSU-30k ( Rank-1 metric) paperswithcode.com computer vision 에서 downstream task 에 대해 ..
논문 리뷰/self-supervised learning 2023. 8. 5. 04:38
[논문 리뷰] CLIP: Learning Transferable Visual Models From Natural Language Supervision(2021)

이번에 리뷰할 논문은 Learning Transferable Visual Models From Natural Language Supervision 입니다. https://arxiv.org/abs/2103.00020 Learning Transferable Visual Models From Natural Language Supervision State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories. This restricted form of supervision limits their generality and usability since additional label..
논문 리뷰/Multi-Modal 2023. 8. 2. 04:12
[논문 리뷰] MoCo: Momentum Contrast for Unsupervised Visual Representation Learning(2020)

이번에 리뷰할 논문은 Momentum Contrast for Unsupervised Visual Representation Learning 입니다. https://paperswithcode.com/paper/momentum-contrast-for-unsupervised-visual Papers with Code - Momentum Contrast for Unsupervised Visual Representation Learning #11 best model for Contrastive Learning on imagenet-1k (ImageNet Top-1 Accuracy metric) paperswithcode.com 본 포스팅을 이해하기 위해서는 "contrast learning" 의 기본적인 이해가 ..
논문 리뷰/self-supervised learning 2023. 8. 2. 00:13
[논문 리뷰] simCLR : A Simple Framework for Contrastive Learning of Visual Representations(2020)

이번에 리뷰할 논문은 A Simple Framework for Contrastive Learning of Visual Representations 입니다. https://paperswithcode.com/paper/a-simple-framework-for-contrastive-learning Papers with Code - A Simple Framework for Contrastive Learning of Visual Representations #4 best model for Contrastive Learning on imagenet-1k (ImageNet Top-1 Accuracy metric) paperswithcode.com 일반적으로 딥러닝 모델은 라벨링된 데이터에 의해 학습을 진행하며, 이를..
논문 리뷰/self-supervised learning 2023. 7. 31. 04:50
[논문 리뷰] ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video(2022)

이번에 리뷰할 논문은 ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video 입니다. https://paperswithcode.com/paper/esfpnet-efficient-deep-learning-architecture Papers with Code - ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchosc #2 best model for Medical Image Segmentation on ETIS-L..
논문 리뷰/Image Segmentation 2023. 7. 30. 01:15
[논문 리뷰] FCBFormer: FCN-Transformer Feature Fusion for Polyp Segmentation(2022)

이번에 리뷰할 논문은 FCN-Transformer Feature Fusion for Polyp Segmentation 입니다. https://paperswithcode.com/paper/fcn-transformer-feature-fusion-for-polyp Papers with Code - FCN-Transformer Feature Fusion for Polyp Segmentation #5 best model for Medical Image Segmentation on Kvasir-SEG (mean Dice metric) paperswithcode.com 본 논문에서 제안하는 FCBFormer모델은 대장 내시경(Colonoscopy) 영상의 대장암(colorectal cancer) 부분의 영역을 검출하..
논문 리뷰/Image Segmentation 2023. 7. 29. 18:12
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