TAME: Attention Mechanism Based Feature Fusion for Generating Explanation Maps of Convolutional Neural Networks

18 January 2023

Papers citing "TAME: Attention Mechanism Based Feature Fusion for Generating Explanation Maps of Convolutional Neural Networks"

6 / 6 papers shown

Title
T-TAME: Trainable Attention Mechanism for Explaining Convolutional Networks and Vision Transformers Mariano V. Ntrougkas Nikolaos Gkalelis Vasileios Mezaris FAtt ViT 25 5 0 07 Mar 2024
Deep spatial context: when attention-based models meet spatial regression Paulina Tomaszewska El.zbieta Sienkiewicz Mai P. Hoang Przemysław Biecek 15 1 0 18 Jan 2024
Explain Any Concept: Segment Anything Meets Concept-Based Explanation Ao Sun Pingchuan Ma Yuanyuan Yuan Shuai Wang LLMAG 20 31 0 17 May 2023
On The Coherence of Quantitative Evaluation of Visual Explanations Benjamin Vandersmissen José Oramas XAI FAtt 26 3 0 14 Feb 2023
Learn To Pay Attention Saumya Jetley Nicholas A. Lord Namhoon Lee Philip H. S. Torr 67 437 0 06 Apr 2018
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay L. Smith 202 1,019 0 26 Mar 2018