Examining CNN Representations with respect to Dataset Bias

Examining CNN Representations with respect to Dataset Bias

29 October 2017

Papers citing "Examining CNN Representations with respect to Dataset Bias"

19 / 19 papers shown

Title
Faithful Counterfactual Visual Explanations (FCVE) Bismillah Khan Syed Ali Tariq Tehseen Zia Muhammad Ahsan David Windridge 44 0 0 12 Jan 2025
Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Syed Ali Tariq Tehseen Zia Mubeen Ghafoor AAML 62 7 0 12 Jan 2025
Zone Evaluation: Revealing Spatial Bias in Object Detection Zhaohui Zheng Yuming Chen Qibin Hou Xiang Li Ping Wang Ming-Ming Cheng ObjD 27 3 0 20 Oct 2023
Discovering and Explaining the Non-Causality of Deep Learning in SAR ATR Wei-Jang Li Wei Yang Li Liu Wenpeng Zhang Yong-Jin Liu 26 24 0 03 Apr 2023
Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries Haekyu Park Seongmin Lee Benjamin Hoover Austin P. Wright Omar Shaikh Rahul Duggal Nilaksh Das Kevin Wenliang Li Judy Hoffman Duen Horng Chau 36 2 0 30 Mar 2022
Concept Embedding Analysis: A Review Gesina Schwalbe 34 28 0 25 Mar 2022
IFBiD: Inference-Free Bias Detection Ignacio Serna Daniel DeAlcala Aythami Morales Julian Fierrez J. Ortega-Garcia CVBM 39 11 0 09 Sep 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 31 0 09 Jun 2021
Deep Learning for Political Science Kakia Chatsiou Slava Jankin AI4CE 39 12 0 13 May 2020
Deceptive AI Explanations: Creation and Detection Johannes Schneider Christian Meske Michalis Vlachos 29 28 0 21 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 43 301 0 08 Jan 2020
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping Xi Yang Bojian Wu Issei Sato Takeo Igarashi CVBM 22 4 0 02 May 2019
Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness Jiawang Bai Yiming Li Jiawei Li Yong Jiang Shutao Xia 37 15 0 14 Mar 2019
Interpretable CNNs for Object Classification Quanshi Zhang Xin Eric Wang Ying Nian Wu Huilin Zhou Song-Chun Zhu 24 54 0 08 Jan 2019
Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering Quanshi Zhang Ruiming Cao Ying Nian Wu Song-Chun Zhu 19 14 0 18 Dec 2018
Explaining Neural Networks Semantically and Quantitatively Runjin Chen Hao Chen Ge Huang Jie Ren Quanshi Zhang FAtt 23 54 0 18 Dec 2018
Counterfactuals uncover the modular structure of deep generative models M. Besserve Arash Mehrjou Rémy Sun Bernhard Schölkopf DRL BDL DiffM 19 107 0 08 Dec 2018
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems Sina Mohseni Niloofar Zarei Eric D. Ragan 36 102 0 28 Nov 2018
Visual Interpretability for Deep Learning: a Survey Quanshi Zhang Song-Chun Zhu FaML HAI 17 810 0 02 Feb 2018