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Updated: May 28, 2025

Deep Neural Networks for Image-Based Dietary Assessment
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Published on: March 13, 2021

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EAMAPG:通过预测梯度下降进行可解释的对抗模型分析.

Ahmad Chaddad1, Yuchen Jiang2, Tareef S Daqqaq3

  • 1Artificial Intelligence for Personalized Medicine, School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin, 541004, China; Laboratory for Imagery, Vision and Artificial Intelligence, École de Technologie Supérieure (ETS), Montreal, H3C 1K3, Canada.

Computers in biology and medicine
|February 13, 2025
PubMed
概括

本研究介绍了使用预测梯度下降 (PGD) 的对抗生成,以提高医疗图像分析中的深度学习 (DL) 模型的可解释性. 该方法确定了影响DL决策的关键特征,提高了放射科医生的透明度.

关键词:
深度学习是一种深度学习.可解释的人工智能预计的梯度下降.

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