ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2102.07799
  4. Cited By
Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of
  Convolutional Neural Networks

Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021
15 February 2021
M. Sudhakar
S. Sattarzadeh
Konstantinos N. Plataniotis
Jongseong Jang
Yeonjeong Jeong
Hyunwoo J. Kim
    AAML
ArXiv (abs)PDFHTML

Papers citing "Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks"

11 / 11 papers shown
P-TAME: Explain Any Image Classifier with Trained Perturbations
P-TAME: Explain Any Image Classifier with Trained PerturbationsIEEE Open Journal of Signal Processing (JOSP), 2025
Mariano V. Ntrougkas
Vasileios Mezaris
Ioannis Patras
AAMLFAtt
235
0
0
29 Jan 2025
T-TAME: Trainable Attention Mechanism for Explaining Convolutional Networks and Vision Transformers
T-TAME: Trainable Attention Mechanism for Explaining Convolutional Networks and Vision Transformers
Mariano V. Ntrougkas
Nikolaos Gkalelis
Vasileios Mezaris
ViTFAtt
233
8
0
07 Mar 2024
LangXAI: Integrating Large Vision Models for Generating Textual
  Explanations to Enhance Explainability in Visual Perception Tasks
LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks
Truong Thanh Hung Nguyen
Tobias Clement
Phuc Truong Loc Nguyen
Nils Kemmerzell
Van Binh Truong
V. Nguyen
Mohamed Abdelaal
Hung Cao
VLM
258
16
0
19 Feb 2024
Towards Better Explanations for Object Detection
Towards Better Explanations for Object DetectionAsian Conference on Machine Learning (ACML), 2023
Van Binh Truong
Hung Truong Thanh Nguyen
Truong Thanh Hung Nguyen
Quoc Khanh Nguyen
Quoc Hung Cao
166
13
0
05 Jun 2023
Towards Trust of Explainable AI in Thyroid Nodule Diagnosis
Towards Trust of Explainable AI in Thyroid Nodule Diagnosis
Hung Truong Thanh Nguyen
Van Binh Truong
V. Nguyen
Quoc Hung Cao
Quoc Khanh Nguyen
101
15
0
08 Mar 2023
On The Coherence of Quantitative Evaluation of Visual Explanations
On The Coherence of Quantitative Evaluation of Visual ExplanationsComputer Vision and Image Understanding (CVIU), 2023
Benjamin Vandersmissen
José Oramas
XAIFAtt
391
6
0
14 Feb 2023
TAME: Attention Mechanism Based Feature Fusion for Generating
  Explanation Maps of Convolutional Neural Networks
TAME: Attention Mechanism Based Feature Fusion for Generating Explanation Maps of Convolutional Neural NetworksIEEE International Symposium on Multimedia (ISM), 2022
Mariano V. Ntrougkas
Nikolaos Gkalelis
Vasileios Mezaris
FAtt
114
9
0
18 Jan 2023
Learning Visual Explanations for DCNN-Based Image Classifiers Using an
  Attention Mechanism
Learning Visual Explanations for DCNN-Based Image Classifiers Using an Attention Mechanism
Ioanna Gkartzonika
Nikolaos Gkalelis
Vasileios Mezaris
138
9
0
22 Sep 2022
ViGAT: Bottom-up event recognition and explanation in video using
  factorized graph attention network
ViGAT: Bottom-up event recognition and explanation in video using factorized graph attention networkIEEE Access (IEEE Access), 2022
Nikolaos Gkalelis
Dimitrios Daskalakis
Vasileios Mezaris
203
12
0
20 Jul 2022
Rethinking gradient weights' influence over saliency map estimation
Rethinking gradient weights' influence over saliency map estimationItalian National Conference on Sensors (INS), 2022
Masud An Nur Islam Fahim
Nazmus Saqib
Shafkat Khan Siam
H. Jung
FAtt
82
1
0
12 Jul 2022
Prototype Learning for Interpretable Respiratory Sound Analysis
Prototype Learning for Interpretable Respiratory Sound Analysis
Zhao Ren
T. Nguyen
Wolfgang Nejdl
429
33
0
07 Oct 2021
1