This Looks Like That, Because ... Explaining Prototypes for
Interpretable Image Recognition

This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition

5 November 2020

Annemarie Jutte

Jesper C. Provoost

Papers citing "This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition"

15 / 15 papers shown

Title
Disentangling Visual Transformers: Patch-level Interpretability for Image Classification Guillaume Jeanneret Loïc Simon F. Jurie ViT 49 0 0 24 Feb 2025
Leveraging Habitat Information for Fine-grained Bird Identification Tin Nguyen Anh Nguyen Anh Nguyen VLM 44 0 0 22 Dec 2023
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations Chiyu Ma Brandon Zhao Chaofan Chen Cynthia Rudin 24 26 0 28 Oct 2023
Natural Example-Based Explainability: a Survey Antonin Poché Lucas Hervier M. Bakkay XAI 28 11 0 05 Sep 2023
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk Joost van de Weijer Bartosz Zieliñski Bartlomiej Twardowski CLL 32 28 0 14 Mar 2023
Stop overkilling simple tasks with black-box models and use transparent models instead Matteo Rizzo Matteo Marcuzzo A. Zangari A. Gasparetto A. Albarelli VLM 21 0 0 06 Feb 2023
Hierarchical Explanations for Video Action Recognition Sadaf Gulshad Teng Long Nanne van Noord FAtt 23 6 0 01 Jan 2023
Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models Poulami Sinhamahapatra Lena Heidemann Maureen Monnet Karsten Roscher 39 5 0 22 Nov 2022
Care for the Mind Amid Chronic Diseases: An Interpretable AI Approach Using IoT Jiaheng Xie Xiaohang Zhao Xiang Liu Xiao Fang OOD 36 2 0 08 Nov 2022
Visual correspondence-based explanations improve AI robustness and human-AI team accuracy Giang Nguyen Mohammad Reza Taesiri Anh Totti Nguyen 30 42 0 26 Jul 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 106 64 0 31 May 2022
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes Jonathan Donnelly A. Barnett Chaofan Chen 3DH 30 127 0 29 Nov 2021
Toward a Unified Framework for Debugging Concept-based Models A. Bontempelli Fausto Giunchiglia Andrea Passerini Stefano Teso 20 4 0 23 Sep 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 653 0 20 Mar 2021
Neural Prototype Trees for Interpretable Fine-grained Image Recognition Meike Nauta Ron van Bree C. Seifert 80 262 0 03 Dec 2020