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Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders

5 February 2021

Harshana Habaragamuwa

Y. Oishi

Kenichi Tanaka

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Papers citing "Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders"

29 / 29 papers shown

Title
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 103 378 0 30 Apr 2020
Concept Whitening for Interpretable Image Recognition Zhi Chen Yijie Bei Cynthia Rudin FAtt 76 320 0 05 Feb 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 121 6,269 0 22 Oct 2019
Interpretable Image Recognition with Hierarchical Prototypes Peter Hase Chaofan Chen Oscar Li Cynthia Rudin VLM 83 111 0 25 Jun 2019
Automatic estimation of heading date of paddy rice using deep learning Sai Vikas Desai V. Balasubramanian T. Fukatsu S. Ninomiya Wei Guo 87 74 0 19 Jun 2019
An Introduction to Variational Autoencoders Diederik P. Kingma Max Welling BDL SSL DRL 89 2,354 0 06 Jun 2019
Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training Xianxu Hou Ke Sun Linlin Shen Guoping Qiu GAN DRL 48 53 0 04 Jun 2019
Deep interpretable architecture for plant diseases classification Mohammed Brahimi Said Mahmoudi K. Boukhalfa A. Moussaoui 41 47 0 31 May 2019
Diagnosing and Enhancing VAE Models Bin Dai David Wipf DRL 63 380 0 14 Mar 2019
Variational Autoencoders Pursue PCA Directions (by Accident) Michal Rolínek Dominik Zietlow Georg Martius OOD DRL 69 152 0 17 Dec 2018
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix Wichmann Wieland Brendel 103 2,670 0 29 Nov 2018
Deep learning in agriculture: A survey A. Kamilaris F. Prenafeta-Boldú 75 3,006 0 31 Jul 2018
Understanding disentangling in $β$ -VAE Christopher P. Burgess I. Higgins Arka Pal Loic Matthey Nicholas Watters Guillaume Desjardins Alexander Lerchner CoGe DRL 68 830 0 10 Apr 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 62 1,350 0 16 Feb 2018
Fader Networks: Manipulating Images by Sliding Attributes Guillaume Lample Neil Zeghidour Nicolas Usunier Antoine Bordes Ludovic Denoyer MarcÁurelio Ranzato DRL GAN 98 545 0 01 Jun 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 188 5,989 0 04 Mar 2017
Deep Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon Kevin Patrick Murphy 126 1,721 0 01 Dec 2016
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 318 20,023 0 07 Oct 2016
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings Tolga Bolukbasi Kai-Wei Chang James Zou Venkatesh Saligrama Adam Kalai CVBM FaML 110 3,139 0 21 Jul 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 159 4,235 0 12 Jun 2016
Using Deep Learning for Image-Based Plant Disease Detection Sharada Mohanty David P. Hughes M. Salathé 43 3,119 0 11 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,990 0 16 Feb 2016
Discriminative Regularization for Generative Models Alex Lamb Vincent Dumoulin Aaron Courville DRL 95 65 0 09 Feb 2016
Ladder Variational Autoencoders C. Sønderby T. Raiko Lars Maaløe Søren Kaae Sønderby Ole Winther BDL DRL 97 912 0 06 Feb 2016
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition G. Montavon Sebastian Lapuschkin Alexander Binder Wojciech Samek Klaus-Robert Muller FAtt 60 737 0 08 Dec 2015
Why are deep nets reversible: A simple theory, with implications for training Sanjeev Arora Yingyu Liang Tengyu Ma 47 54 0 18 Nov 2015
From Facial Parts Responses to Face Detection: A Deep Learning Approach Shuo Yang Ping Luo Chen Change Loy Xiaoou Tang CVBM 76 570 0 22 Sep 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 248 4,672 0 21 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,386 0 04 Sep 2014