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[CAM 논문 리뷰] - Learning Deep Features for Discriminative Localization *XAI에서 가장 대표적으로 쓰이는 CAM 논문 리뷰입니다. 궁금하신 점은 댓글로 남겨주세요. CAM paper: [1512.04150] Learning Deep Features for Discriminative Localization (arxiv.org) Learning Deep Features for Discriminative Localization In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network to have remarkable localization ability despit..
[DETR 논문 리뷰] - End-to-End Object Detection with Transformers *DETR 논문 리뷰를 위한 글입니다! 궁금하신 점이 있다면 댓글로 남겨주세요. DETR paper: [2005.12872] End-to-End Object Detection with Transformers (arxiv.org) End-to-End Object Detection with Transformers We present a new method that views object detection as a direct set prediction problem. Our approach streamlines the detection pipeline, effectively removing the need for many hand-designed components like a non-maximum supp..
[TransUNet 논문 리뷰] - TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation *TransUNet 논문 리뷰를 위한 글이고, 질문이 있으시다면 언제든지 댓글로 남겨주세요! TransUNet paper: [2102.04306] TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation (arxiv.org) TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Medical image segmentation is an essential prerequisite for developing healthcare systems, especially for disease diagnosis and treatment planning. On v..

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