Trustworthy Convolutional Neural Networks: A Gradient Penalized-based Approach

29 September 2020

Papers citing "Trustworthy Convolutional Neural Networks: A Gradient Penalized-based Approach"

7 / 7 papers shown

Title
Ovarian Cancer Data Analysis using Deep Learning: A Systematic Review from the Perspectives of Key Features of Data Analysis and AI Assurance Muta Tah Hira M. Razzaque Mosharraf Sarker 19 0 0 20 Nov 2023
Distance-Aware eXplanation Based Learning Misgina Tsighe Hagos Niamh Belton Kathleen M. Curran Brian Mac Namee FAtt 23 0 0 11 Sep 2023
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning Yuyang Gao Siyi Gu Junji Jiang S. Hong Dazhou Yu Liang Zhao 24 39 0 07 Dec 2022
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 27 65 0 15 Nov 2021
Defense Against Explanation Manipulation Ruixiang Tang Ninghao Liu Fan Yang Na Zou Xia Hu AAML 39 11 0 08 Nov 2021
Split and Expand: An inference-time improvement for Weakly Supervised Cell Instance Segmentation Lin Geng Foo Rui En Ho Jiamei Sun Alexander Binder 11 0 0 21 Jul 2020
Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning Models Jiamei Sun Sebastian Lapuschkin Wojciech Samek Alexander Binder FAtt 31 29 0 04 Jan 2020