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Tayyaba Azim
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
- [j7]Navamayooran Thavanesan
, Arya Farahi
Insights from explainable AI in oesophageal cancer team decisions. Comput. Biol. Medicine 180: 108978 (2024) - [c9]Loitongbam Gyanendro Singh, Stuart E. Middleton, Tayyaba Azim, Elena Nichele, Pinyi Lyu, Santiago De Ossorno Garcia:
ConversationMoC: Encoding Conversational Dynamics using Multiplex Network for Identifying Moment of Change in Mood and Mental Health Classification. ML4CMH@AAAI 2024: 42-56 - 2023
- [c8]Jennifer Williams
Socio-Technical Trust For Multi-Modal Hearing Assistive Technology. ICASSP Workshops 2023: 1-5 - 2022
- [c7]Sarah Ahmed, Tayyaba Azim
Revisiting Deep Fisher Vectors: Using Fisher Information to Improve Object Classification. BMVC 2022: 900 - 2021
- [j6]Shakeel Shafiq, Tayyaba Azim
Introspective analysis of convolutional neural networks for improving discrimination performance and feature visualisation. PeerJ Comput. Sci. 7: e497 (2021) - 2020
- [j5]Sarah Ahmed, Tayyaba Azim
Diversified Fisher kernel: encoding discrimination in Fisher features to compete deep neural models for visual classification task. IET Comput. Vis. 14(8): 658-664 (2020)
2010 – 2019
- 2019
- [j4]Huma Samin
Knowledge Based Recommender System for Academia Using Machine Learning: A Case Study on Higher Education Landscape of Pakistan. IEEE Access 7: 67081-67093 (2019) - [j3]Bibi Amina
SCANCPECLENS: A Framework for Automatic Lexicon Generation and Sentiment Analysis of Micro Blogging Data on China Pakistan Economic Corridor. IEEE Access 7: 133876-133887 (2019) - 2018
- [b2]Tayyaba Azim
Composing Fisher Kernels from Deep Neural Models - A Practitioner's Approach. Springer Briefs in Computer Science, Springer 2018, ISBN 978-3-319-98523-7, pp. 1-59 - 2017
- [c6]Sarah Ahmed, Tayyaba Azim:
Condensing Deep Fisher Vectors: To Choose or to Compress? ICPRAM (Revised Selected Papers) 2017: 80-98 - [c5]Sarah Ahmed, Tayyaba Azim
Compression Techniques for Deep Fisher Vectors. ICPRAM 2017: 217-224 - 2014
- [b1]Tayyaba Azim
Visual scene recognition with biologically relevant generative models. University of Southampton, UK, 2014 - [j2]Kaya Kuru
Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics. Artif. Intell. Medicine 62(2): 105-118 (2014) - [j1]Tayyaba Azim
Fully automated real time fatigue detection of drivers through Fuzzy Expert Systems. Appl. Soft Comput. 18: 25-38 (2014) - [c4]Tayyaba Azim
Computational Models of Object Recognition - Goal, Role and Success. VISAPP (1) 2014: 179-186 - [c3]Tayyaba Azim
Texture Classification with Fisher Kernel Extracted from the Continuous Models of RBM. VISAPP (2) 2014: 684-690 - 2013
- [c2]Tayyaba Azim
Inducing discrimination in biologically inspired models of visual scene recognition. MLSP 2013: 1-6
2000 – 2009
- 2009
- [c1]Tayyaba Azim, M. Arfan Jaffar, Muhammad Ramzan
Automatic Fatigue Detection of Drivers through Yawning Analysis. FGIT-SIP 2009: 125-132
Coauthor Index
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