Adjusting Amount of AI Explanation for Visual Tasks-Reference-Cited by-同舟云学术

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Adjusting Amount of AI Explanation for Visual Tasks

Published:2024-05-11 Issue: Volume: Page:1-7
ISSN:
Container-title:Extended Abstracts of the CHI Conference on Human Factors in Computing Systems
language:
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Author:

Maehigashi Akihiro¹^ORCID,Fukuchi Yosuke²^ORCID,Yamada Seiji³^ORCID

Affiliation:

1. Center for Research and Development in Admissions, Shizuoka University, Japan

2. Digital Content and Media Sciences Research Division, National Institute of Informatics, Japan

3. National Institute of Informatics, Japan and Department of Informatics, SOKENDAI (The Graduate University for Advanced Studies), Japan

Funder

Japan Science and Technology Agency, CREST

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613905.3650802

Reference40 articles.

1. Towards automatic threat detection: A survey of advances of deep learning within X-ray security imaging

2. How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare

3. Introduction of human-centric AI assistant to aid radiologists for multimodal breast image classification

4. Understanding User Reliance on AI in Assisted Decision-Making

5. Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks

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