BarkXAI: A Lightweight Post-Hoc Explainable Method for Tree Species Classification with Quantifiable Concepts

26 February 2025

Papers citing "BarkXAI: A Lightweight Post-Hoc Explainable Method for Tree Species Classification with Quantifiable Concepts"

6 / 6 papers shown

Title
Concept-Attention Whitening for Interpretable Skin Lesion Diagnosis Junlin Hou Jilan Xu Hao Chen MedIm 69 8 0 09 Apr 2024
Now You See Me (CME): Concept-based Model Extraction Dmitry Kazhdan B. Dimanov M. Jamnik Pietro Lio Adrian Weller 46 75 0 25 Oct 2020
Tree bark re-identification using a deep-learning feature descriptor Martine Robert Patrick Dallaire Philippe Giguère 46 9 0 06 Dec 2019
Tree Species Identification from Bark Images Using Convolutional Neural Networks Mathieu Carpentier Philippe Giguère Jonathan Gaudreault 54 59 0 02 Mar 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 217 1,842 0 30 Nov 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,939 0 22 May 2017