Items where Author is "Altahhan, A"
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Altahhan, A (2020) True Online TD(λ)-Replan Method Planning Through Replaying. In: International Joint Conference of Neural Networks, IJCNN 2020, 19-24 Jul 2020, Scotland.
Shackleton, A and Altahhan, A (2019) "A Comparison Study of Deep Learning Techniques to Increase the Spatial Resolution of Photo-Realistic Images." In: Neural Information Processing. ICONIP 2019. Communications in Computer and Information Science, 1142 . Springer Verlag (Germany). ISBN 978-3-030-36807-4 DOI: https://doi.org/10.1007/978-3-030-36808-1_37
Altahhan, A (2018) TD(0)-Replay: An Efficient Model-Free Planning with full Replay. Proceedings of International Joint Conference on Neural Networks. ISSN 2161-4393 DOI: https://doi.org/10.1109/IJCNN.2018.8489300
Ruiz-Garcia, A and Elshaw, M and Altahhan, A and Palade, V (2018) A hybrid deep learning neural approach for emotion recognition from facial expressions for socially assistive robots. Neural Computing and Applications, 29 (7). pp. 359-373. ISSN 0941-0643 DOI: https://doi.org/10.1007/s00521-018-3358-8
Altahhan, A (2016) Self-reflective deep reinforcement learning. Proceedings of the International Joint Conference on Neural Networks. pp. 4565-4570. ISSN 2161-4407 DOI: https://doi.org/10.1109/IJCNN.2016.7727798
Altahhan, A (2015) Deep feature-action processing with mixture of updates. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9492. pp. 1-10. ISSN 0302-9743 DOI: https://doi.org/10.1007/978-3-319-26561-2_1
Altahhan, A and Alizadeh, J and Holms, B (2013) Course Learning Outcome Accreditation Tool: Supporting the Measurement of Classroom Learning. In: International Conference of Technology and Business Management ICTBM2013, Dubai, UAE. (Unpublished)
Altahhan, A (2011) "A robot visual homing model that traverses conjugate gradient TD to a variable λ TD and uses radial basis features." In: Mellouk, A, (ed.) Advances in Reinforcement Learning. INTECH, pp. 225-254. ISBN 978-953-307-369-9 DOI: https://doi.org/10.5772/13817