What do Deep Networks Like to See?

What do Deep Networks Like to See?

22 March 2018

Sebastián M. Palacio

ArXiv (abs)PDF HTML

Papers citing "What do Deep Networks Like to See?"

17 / 17 papers shown

Title
Bayesian and Convolutional Networks for Hierarchical Morphological Classification of Galaxies Jonathan Serrano-Pérez Raquel Díaz-Hernández L. Sucar 51 1 0 03 May 2024
DreamCatcher: Revealing the Language of the Brain with fMRI using GPT Embedding Subhrasankar Chatterjee D. Samanta 97 4 0 16 Jun 2023
XAI Handbook: Towards a Unified Framework for Explainable AI Sebastián M. Palacio Adriano Lucieri Mohsin Munir Jörn Hees Sheraz Ahmed Andreas Dengel 56 32 0 14 May 2021
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space Shihao Zhao Xingjun Ma Yisen Wang James Bailey Yue Liu Yu-Gang Jiang AAML 56 15 0 18 Jan 2021
A Study of Image Pre-processing for Faster Object Recognition Md. Tanzil Shahriar Huyue Li 10 7 0 31 Oct 2020
P2ExNet: Patch-based Prototype Explanation Network Dominique Mercier Andreas Dengel Sheraz Ahmed 36 4 0 05 May 2020
On Interpretability of Deep Learning based Skin Lesion Classifiers using Concept Activation Vectors Adriano Lucieri Muhammad Naseer Bajwa S. Braun M. I. Malik Andreas Dengel Sheraz Ahmed MedIm 241 65 0 05 May 2020
TSInsight: A local-global attribution framework for interpretability in time-series data Shoaib Ahmed Siddiqui Dominique Mercier Andreas Dengel Sheraz Ahmed FAtt AI4TS 48 12 0 06 Apr 2020
Exploring Simple and Transferable Recognition-Aware Image Processing Zhuang Liu H. Wang Tinghui Zhou Zhiqiang Shen Bingyi Kang Evan Shelhamer Trevor Darrell 56 9 0 21 Oct 2019
Refining 6D Object Pose Predictions using Abstract Render-and-Compare Arul Selvam Periyasamy Max Schwarz Sven Behnke 50 17 0 08 Oct 2019
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data Divyansh Kaushik Eduard H. Hovy Zachary Chase Lipton CML 110 571 0 26 Sep 2019
What do Deep Networks Like to Read? Jonas Pfeiffer Aishwarya Kamath Iryna Gurevych Sebastian Ruder 47 3 0 10 Sep 2019
LIP: Local Importance-based Pooling Ziteng Gao Limin Wang Gangshan Wu FAtt 85 96 0 12 Aug 2019
Similarity-preserving Image-image Domain Adaptation for Person Re-identification Weijian Deng Liang Zheng QiXiang Ye Yi Yang Jianbin Jiao GAN 40 16 0 26 Nov 2018
Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations Tianlu Wang Jieyu Zhao Mark Yatskar Kai-Wei Chang Vicente Ordonez FaML 103 17 0 20 Nov 2018
An Overview of Computational Approaches for Interpretation Analysis Philipp Blandfort Jörn Hees D. Patton 49 2 0 09 Nov 2018
Adversarial Defense based on Structure-to-Signal Autoencoders Joachim Folz Sebastián M. Palacio Jörn Hees Damian Borth Andreas Dengel AAML 71 32 0 21 Mar 2018