| 일 | 월 | 화 | 수 | 목 | 금 | 토 |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| 9 | 10 | 11 | 12 | 13 | 14 | 15 |
| 16 | 17 | 18 | 19 | 20 | 21 | 22 |
| 23 | 24 | 25 | 26 | 27 | 28 | 29 |
| 30 | 31 |
- 설명가능한 인공지능
- meta-learning
- keras
- Score-CAM
- python
- cs231n
- Unsupervised learning
- Artificial Intelligence
- Explainable AI
- AI
- xai
- Interpretability
- 시계열 분석
- 머신러닝
- 메타러닝
- Class activation map
- 코딩 테스트
- SmoothGrad
- Deep learning
- Cam
- 코딩테스트
- 백준
- 설명가능한
- GAN
- 딥러닝
- 기계학습
- coding test
- Machine Learning
- grad-cam
- 인공지능
- Today
- Total
목록Score-CAM (3)
iMTE
Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks 내용 정리 [XAI-11]
논문 제목 : Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks 논문 주소 : https://arxiv.org/abs/2103.13859 Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks In this paper, we propose an efficient saliency map generation method, called Group score-weighted Class Activation Mapping (Group-CAM), which adopts the "split-transform-merge" str..
SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization 내용 정리 [XAI-10]
논문 제목 : SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization 논문 주소 : https://arxiv.org/abs/2006.14255 SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization Interpretation of the underlying mechanisms of Deep Convolutional Neural Networks has become an important aspect of research in the field of deep learning due to their applications in high-risk environments. To expl..
Score-CAM : Score-weighted visual explanations for convolutional neural networks [XAI-9]
논문 제목 : Score-CAM : Score-weighted visual explanations for convolutional neural networks 논문 주소 : https://openaccess.thecvf.com/content_CVPRW_2020/html/w1/Wang_Score-CAM_Score-Weighted_Visual_Explanations_for_Convolutional_Neural_Networks_CVPRW_2020_paper.html CVPR 2020 Open Access Repository Haofan Wang, Zifan Wang, Mengnan Du, Fan Yang, Zijian Zhang, Sirui Ding, Piotr Mardziel, Xia Hu; Proceedi..