Challenging the Black Box: A Comprehensive Evaluation of Attribution
Maps of CNN Applications in Agriculture and Forestry

Challenging the Black Box: A Comprehensive Evaluation of Attribution Maps of CNN Applications in Agriculture and Forestry

18 February 2024

Henrike Stephani

Jördis Sieburg-Rockel

Stephanie Helmling

Papers citing "Challenging the Black Box: A Comprehensive Evaluation of Attribution Maps of CNN Applications in Agriculture and Forestry"

6 / 6 papers shown

Title
Reliable Evaluation of Attribution Maps in CNNs: A Perturbation-Based Approach Lars Nieradzik Henrike Stephani J. Keuper FAtt 71 1 0 22 Nov 2024
Metrics for saliency map evaluation of deep learning explanation methods T. Gomez Thomas Fréour Harold Mouchère XAI FAtt 59 41 0 31 Jan 2022
Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis Samuele Poppi Marcella Cornia Lorenzo Baraldi Rita Cucchiara FAtt 125 33 0 20 Apr 2021
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 134 656 0 28 Dec 2020
Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels Xiangwei Shi Seyran Khademi Yun-qiang Li J. C. V. Gemert VLM WSOL 38 19 0 16 Oct 2020
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,237 0 25 Aug 2016