Using Causal Analysis for Conceptual Deep Learning Explanation
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-87199-4_49
Reference23 articles.
1. Basu, S., Mitra, S., Saha, N.: Deep learning for screening COVID-19 using chest X-ray images. In: IEEE Symposium Series on Computational Intelligence (SSCI) (2020)
2. Bau, D., Zhou, B., Khosla, A., Oliva, A., Torralba, A.: Network dissection: quantifying interpretability of deep visual representations. In: IEEE Computer Vision and Pattern Recognition (CVPR), pp. 6541–6549 (2017)
3. Bau, D., Zhu, J.Y., Strobelt, H., Lapedriza, A., Zhou, B., Torralba, A.: Understanding the role of individual units in a deep neural network. Nat. Acad. Sci. 117(48), 30071–30078 (2020)
4. Clough, J.R., Oksuz, I., Puyol-Antón, E., Ruijsink, B., King, A.P., Schnabel, J.A.: Global and local interpretability for cardiac MRI classification. In: Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 656–664 (2019)
5. Glass, A., McGuinness, D.L., Wolverton, M.: Toward establishing trust in adaptive agents. In: International Conference on Intelligent User Interfaces (2008)
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Unveiling the black box: A systematic review of Explainable Artificial Intelligence in medical image analysis;Computational and Structural Biotechnology Journal;2024-12
2. A study of criteria for grading follicular lymphoma using a cell type classifier from pathology images based on complementary-label learning;Micron;2024-09
3. Counter-CAM : An Improved Grad-CAM based Visual Explainer for Infrared Breast cancer Classification;2023 IEEE 20th India Council International Conference (INDICON);2023-12-14
4. Improving Causality in Interpretable Video Retrieval;20th International Conference on Content-based Multimedia Indexing;2023-09-20
5. Explainable AI: current status and future potential;European Radiology;2023-08-17
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3