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TorchEsegeta: Framework for Interpretability and Explainability of
  Image-based Deep Learning Models

TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models

16 October 2021
S. Chatterjee
Arnab Das
Chirag Mandal
Budhaditya Mukhopadhyay
Manish Vipinraj
Aniruddh Shukla
R. Rao
Chompunuch Sarasaen
Oliver Speck
A. Nürnberger
    MedIm
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Papers citing "TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models"

3 / 3 papers shown
Title
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and
  Beyond: A Survey
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey
Rokas Gipiškis
Chun-Wei Tsai
Olga Kurasova
54
5
0
02 May 2024
Weakly-supervised segmentation using inherently-explainable
  classification models and their application to brain tumour classification
Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification
S. Chatterjee
Hadya Yassin
Florian Dubost
A. Nürnberger
Oliver Speck
13
4
0
10 Jun 2022
Exploration of Interpretability Techniques for Deep COVID-19
  Classification using Chest X-ray Images
Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images
S. Chatterjee
Fatima Saad
Chompunuch Sarasaen
Suhita Ghosh
Valerie Krug
...
P. Radeva
G. Rose
Sebastian Stober
Oliver Speck
A. Nürnberger
19
25
0
03 Jun 2020
1