| Explaining convolutional neural networks through attribution-based input sampling and block-wise feature aggregation S Sattarzadeh, M Sudhakar, A Lem, S Mehryar, KN Plataniotis, J Jang, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11639 …, 2021 | 21 | 2021 |
| Integrated grad-CAM: Sensitivity-aware visual explanation of deep convolutional networks via integrated gradient-based scoring S Sattarzadeh, M Sudhakar, KN Plataniotis, J Jang, Y Jeong, H Kim ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 14 | 2021 |
| Ada-SISE: adaptive semantic input sampling for efficient explanation of convolutional neural networks M Sudhakar, S Sattarzadeh, KN Plataniotis, J Jang, Y Jeong, H Kim ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 7 | 2021 |
| SVEA: A Small-scale Benchmark for Validating the Usability of Post-hoc Explainable AI Solutions in Image and Signal Recognition S Sattarzadeh, M Sudhakar, KN Plataniotis Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 4 | 2021 |
| Semantic input sampling for explanation (sise) of convolutional neural networks J Jongseong, H Kim, YJ Jeong, S Lee, S Sattarzadeh, M Sudhakar, ... US Patent App. 17/405,935, 2022 | | 2022 |
Konstantinos N PlataniotisProfessor, ECE Department, University of TorontoVerified email at ece.utoronto.ca
