ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2405.01636
  4. Cited By
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

2 May 2024
Rokas Gipiškis
Chun-Wei Tsai
Olga Kurasova
ArXiv (abs)PDFHTML

Papers citing "Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey"

32 / 82 papers shown
Title
Deep Multi-modal Object Detection and Semantic Segmentation for
  Autonomous Driving: Datasets, Methods, and Challenges
Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges
Di Feng
Christian Haase-Schuetz
Lars Rosenbaum
Heinz Hertlein
Claudius Gläser
Fabian Duffhauss
W. Wiesbeck
Klaus C. J. Dietmayer
3DPC
132
1,013
0
21 Feb 2019
Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted
  by the International Skin Imaging Collaboration (ISIC)
Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)
Noel Codella
V. Rotemberg
P. Tschandl
M. E. Celebi
Stephen W. Dusza
...
Aadi Kalloo
Konstantinos Liopyris
Michael Marchetti
Harald Kittler
Allan Halpern
113
1,193
0
09 Feb 2019
The Liver Tumor Segmentation Benchmark (LiTS)
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic
P. Christ
Hongwei Bran Li
Eugene Vorontsov
Avi Ben-Cohen
...
L. Soler
Bram van Ginneken
H. Greenspan
Leo Joskowicz
Bjoern Menze
126
1,028
0
13 Jan 2019
Metrics for Explainable AI: Challenges and Prospects
Metrics for Explainable AI: Challenges and Prospects
R. Hoffman
Shane T. Mueller
Gary Klein
Jordan Litman
XAI
88
730
0
11 Dec 2018
Sanity Checks for Saliency Maps
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAttAAMLXAI
152
1,970
0
08 Oct 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition
This Looks Like That: Deep Learning for Interpretable Image Recognition
Chaofan Chen
Oscar Li
Chaofan Tao
A. Barnett
Jonathan Su
Cynthia Rudin
250
1,188
0
27 Jun 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models
RISE: Randomized Input Sampling for Explanation of Black-box Models
Vitali Petsiuk
Abir Das
Kate Saenko
FAtt
188
1,176
0
19 Jun 2018
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
Feng Yu
Haofeng Chen
Xin Wang
Wenqi Xian
Yingying Chen
Fangchen Liu
Vashisht Madhavan
Trevor Darrell
VLM
346
2,158
0
12 May 2018
The (Un)reliability of saliency methods
The (Un)reliability of saliency methods
Pieter-Jan Kindermans
Sara Hooker
Julius Adebayo
Maximilian Alber
Kristof T. Schütt
Sven Dähne
D. Erhan
Been Kim
FAttXAI
109
688
0
02 Nov 2017
Counterfactual Explanations without Opening the Black Box: Automated
  Decisions and the GDPR
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
Sandra Wachter
Brent Mittelstadt
Chris Russell
MLAU
135
2,366
0
01 Nov 2017
Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017
  International Symposium on Biomedical Imaging (ISBI), Hosted by the
  International Skin Imaging Collaboration (ISIC)
Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)
Noel Codella
D. Gutman
M. E. Celebi
Brian Helba
Michael Marchetti
...
Aadi Kalloo
Konstantinos Liopyris
N. Mishra
Harald Kittler
Allan Halpern
97
2,082
0
13 Oct 2017
Explanation in Artificial Intelligence: Insights from the Social
  Sciences
Explanation in Artificial Intelligence: Insights from the Social Sciences
Tim Miller
XAI
254
4,281
0
22 Jun 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
22,090
0
22 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual
  Representations
Network Dissection: Quantifying Interpretability of Deep Visual Representations
David Bau
Bolei Zhou
A. Khosla
A. Oliva
Antonio Torralba
MILMFAtt
158
1,526
1
19 Apr 2017
Adversarial Examples for Semantic Segmentation and Object Detection
Adversarial Examples for Semantic Segmentation and Object Detection
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Yuyin Zhou
Lingxi Xie
Alan Yuille
GANAAML
111
934
0
24 Mar 2017
Look into Person: Self-supervised Structure-sensitive Learning and A New
  Benchmark for Human Parsing
Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing
Ke Gong
Xiaodan Liang
Dongyu Zhang
Xiaohui Shen
Liang Lin
SSL
68
477
0
16 Mar 2017
Adversarial Examples for Semantic Image Segmentation
Adversarial Examples for Semantic Image Segmentation
Volker Fischer
Mummadi Chaithanya Kumar
J. H. Metzen
Thomas Brox
SSegGANAAML
93
119
0
03 Mar 2017
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using
  Cascaded Fully Convolutional Neural Networks
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks
P. Christ
Florian Ettlinger
Felix Grün
M. Elshaer
Jana Lipkova
...
Julian Holch
Wieland Sommer
R. Braren
V. Heinemann
Bjoern Menze
MedIm
65
330
0
20 Feb 2017
A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images
A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images
David Vázquez
Jorge Bernal
F. Sánchez
Gloria Fernández-Esparrach
Antonio M. López
Adriana Romero
M. Drozdzal
Aaron Courville
3DV
178
642
0
02 Dec 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
335
20,110
0
07 Oct 2016
Semantic Understanding of Scenes through the ADE20K Dataset
Semantic Understanding of Scenes through the ADE20K Dataset
Bolei Zhou
Hang Zhao
Xavier Puig
Tete Xiao
Sanja Fidler
Adela Barriuso
Antonio Torralba
SSeg
408
1,891
0
18 Aug 2016
Concrete Problems in AI Safety
Concrete Problems in AI Safety
Dario Amodei
C. Olah
Jacob Steinhardt
Paul Christiano
John Schulman
Dandelion Mané
253
2,405
0
21 Jun 2016
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets,
  Atrous Convolution, and Fully Connected CRFs
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
Iasonas Kokkinos
Kevin Patrick Murphy
Alan Yuille
SSeg
273
18,284
0
02 Jun 2016
The Cityscapes Dataset for Semantic Urban Scene Understanding
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts
Mohamed Omran
Sebastian Ramos
Timo Rehfeld
Markus Enzweiler
Rodrigo Benenson
Uwe Franke
Stefan Roth
Bernt Schiele
1.1K
11,654
0
06 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
Learning Deep Features for Discriminative Localization
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSLSSegFAtt
253
9,342
0
14 Dec 2015
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image
  Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
1.1K
15,821
0
02 Nov 2015
Striving for Simplicity: The All Convolutional Net
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
254
4,681
0
21 Dec 2014
Deep Learning Face Attributes in the Wild
Deep Learning Face Attributes in the Wild
Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
253
8,429
0
28 Nov 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
434
43,832
0
01 May 2014
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
317
7,321
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAttSSL
603
15,907
0
12 Nov 2013
Previous
12