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Explanation methods facilitate the development of models that learn meaningful concepts and avoid exploiting spurious correlations.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Semantic contours from inverse detectors
Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev, Subhransu Maji, and Jitendra Malik · 2011
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Explainable multiple abnormality classification of chest ct volumes with axialnet and hirescam
Rachel Lea Draelos and Lawrence Carin · 2012
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2014
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Visualizing and understanding convolutional networks
Matthew D Zeiler and Rob Fergus · 2014
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Striving for simplicity: The all convolutional net
Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, and Martin Riedmiller · 2014
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On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
Sebastian Bach, Alexander Binder, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller, and Wojciech Samek · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Not just a black box: Learning important features through propagating activation differences
Avanti Shrikumar, Peyton Greenside, Anna Shcherbina, and Anshul Kundaje · 2016
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Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
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Seed, expand and constrain: Three principles for weakly-supervised image segmentation
Alexander Kolesnikov and Christoph H Lampert · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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The shattered gradients problem: If resnets are the answer, then what is the question?
David Balduzzi, Marcus Frean, Lennox Leary, JP Lewis, Kurt Wan-Duo Ma, and Brian McWilliams · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study
John R Zech, Marcus A Badgeley, Manway Liu, Anthony B Costa, Joseph J Titano, and Eric Karl Oermann · 2018
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Dynamic routing on deep neural network for thoracic disease classification and sensitive area localization
Yan Shen and Mingchen Gao · 2018
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A theoretical explanation for perplexing behaviors of backpropagation-based visualizations
Weili Nie, Yang Zhang, and Ankit Patel · 2018
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Efficient deep network architectures for fast chest x-ray tuberculosis screening and visualization
F Pasa, V Golkov, F Pfeiffer, D Cremers, and D Pfeiffer · 2019
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Deep learning to assess long-term mortality from chest radiographs
Michael T Lu, Alexander Ivanov, Thomas Mayrhofer, Ahmed Hosny, Hugo JWL Aerts, and Udo Hoffmann · 2019
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Gradient-based attribution methods
Marco Ancona, Enea Ceolini, Cengiz Öztireli, and Markus Gross · 2019
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Integral object mining via online attention accumulation
Peng-Tao Jiang, Qibin Hou, Yang Cao, Ming-Ming Cheng, Yunchao Wei, and Hong-Kai Xiong · 2019
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Ficklenet: Weakly and semi-supervised semantic image segmentation using stochastic inference
Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, and Sungroh Yoon · 2019
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Racial discrimination in face recognition technology
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Julius Adebayo, Justin Gilmer, Michael Muelly, Ian Goodfellow, Moritz Hardt, and Been Kim · 2018
Cited alongside, same era.
Weakly-supervised semantic segmentation by iteratively mining common object features
Xiang Wang, Shaodi You, Xi Li, and Huimin Ma · 2018
Cited alongside, same era.
Weakly-supervised semantic segmentation network with deep seeded region growing
Zilong Huang, Xinggang Wang, Jiasi Wang, Wenyu Liu, and Jingdong Wang · 2018
Cited alongside, same era.
Revisiting dilated convolution: A simple approach for weakly-and semi-supervised semantic segmentation
Yunchao Wei, Huaxin Xiao, Honghui Shi, Zequn Jie, Jiashi Feng, and Thomas S Huang · 2018
Cited alongside, same era.
Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation
Jiwoon Ahn and Suha Kwak · 2018
Cited alongside, same era.
Tell me where to look: Guided attention inference network
Kunpeng Li, Ziyan Wu, Kuan-Chuan Peng, Jan Ernst, and Yun Fu · 2018
Cited alongside, same era.
Unmasking clever hans predictors and assessing what machines really learn
Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, and Klaus-Robert Müller · 2019
Cited alongside, same era.
Alex Najibi · 2020
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A deep learning and grad-cam based color visualization approach for fast detection of covid-19 cases using chest x-ray and ct-scan images
Harsh Panwar, PK Gupta, Mohammad Khubeb Siddiqui, Ruben Morales-Menendez, Prakhar Bhardwaj, and Vaishnavi Singh · 2020
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Self-supervised equivariant attention mechanism for weakly supervised semantic segmentation
Yude Wang, Jie Zhang, Meina Kan, Shiguang Shan, and Xilin Chen · 2020
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Learning integral objects with intra-class discriminator for weakly-supervised semantic segmentation
Junsong Fan, Zhaoxiang Zhang, Chunfeng Song, and Tieniu Tan · 2020
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Cian: Cross-image affinity net for weakly supervised semantic segmentation
Junsong Fan, Zhaoxiang Zhang, Tieniu Tan, Chunfeng Song, and Jun Xiao · 2020
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Mixup-cam: Weakly-supervised semantic segmentation via uncertainty regularization
Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, and Ming-Hsuan Yang · 2020
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Weakly-supervised semantic segmentation via sub-category exploration
Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, and Ming-Hsuan Yang · 2020
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Puzzle-cam: Improved localization via matching partial and full features
Sanhyun Jo and In-Jae Yu · 2021
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Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes
Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, and Lawrence Carin · 2021
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