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pro vyhledávání: '"Muddamsetty, Satya M."'
Autor:
Jahromi, Mohammad N. S., Muddamsetty, Satya. M., Jarlner, Asta Sofie Stage, Høgenhaug, Anna Murphy, Gammeltoft-Hansen, Thomas, Moeslund, Thomas B.
Explainable AI (XAI) aids in deciphering 'black-box' models. While several methods have been proposed and evaluated primarily in the image domain, the exploration of explainability in the text domain remains a growing research area. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2402.03043
Autor:
Jahromi, Mohammad N.S., Muddamsetty, Satya M., Jarlner, Asta Sofie Stage, Høgenhaug, Anna Murphy, Gammeltoft-Hansen, Thomas, Moeslund, Thomas B.
Publikováno v:
In Natural Language Processing Journal June 2024 7
Autor:
Muddamsetty, Satya M., Jahromi, Mohammad N. S., Ciontos, Andreea E., Fenoy, Laura M., Moeslund, Thomas B.
Publikováno v:
Pattern Recognition 127 (2022): 108604
Explainable Artificial Intelligence (XAI) has in recent years become a well-suited framework to generate human understandable explanations of "black-box" models. In this paper, a novel XAI visual explanation algorithm known as the Similarity Differen
Externí odkaz:
http://arxiv.org/abs/2101.10710
A new brand of technical artificial intelligence ( Explainable AI ) research has focused on trying to open up the 'black box' and provide some explainability. This paper presents a novel visual explanation method for deep learning networks in the for
Externí odkaz:
http://arxiv.org/abs/2006.03122
Autor:
Muddamsetty, Satya M., Jahromi, Mohammad N.S., Ciontos, Andreea E., Fenoy, Laura M., Moeslund, Thomas B.
Publikováno v:
In Pattern Recognition July 2022 127
Autor:
Richmond, Karen McGregor, Muddamsetty, Satya M., Gammeltoft-Hansen, Thomas, Olsen, Henrik Palmer, Moeslund, Thomas B.
Publikováno v:
Digital Society; April 2024, Vol. 3 Issue: 1
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Publikováno v:
2015 IEEE International Conference on Image Processing (ICIP); 2015, p427-431, 5p
Publikováno v:
2014 22nd International Conference on Pattern Recognition; 2014, p2353-2358, 6p
Publikováno v:
2013 IEEE International Conference on Image Processing; 2013, p3924-3928, 5p