Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Thiab R. Taha"'
Autor:
Saeid Safaei, Zerotti Woods, Khaled Rasheed, Thiab R. Taha, Vahid Safaei, Juan B. Gutierrez, Hamid R. Arabnia
Publikováno v:
IEEE Access, Vol 12, Pp 73363-73375 (2024)
Deep learning techniques have demonstrated significant capabilities across numerous applications, with deep neural networks (DNNs) showing promising results. However, training these networks efficiently, especially when determining the most suitable
Externí odkaz:
https://doaj.org/article/bc878b86af9940c382aabfe5c08372f1
Publikováno v:
IEEE Access, Vol 8, Pp 218386-218400 (2020)
Methodologies that utilize Deep Learning offer great potential for applications that automatically attempt to generate captions or descriptions about images and video frames. Image and video captioning are considered to be intellectually challenging
Externí odkaz:
https://doaj.org/article/2b40405aa3404cb2adb4b49b7a041ce3
Publikováno v:
Network Biology, Vol 2, Iss 1, Pp 26-37 (2012)
We present GKIN, a simulator and a comprehensive graphical interface where one can draw the model specification of reactions between hypothesized molecular participants in a gene regulatory and biochemical reaction network (or genetic network for sho
Externí odkaz:
https://doaj.org/article/bab4b7ed8e754a5fad902818413cfc71
Autor:
Mehdi Assefi, Mehdi Bahrami, Sarthak Arora, Thiab R. Taha, Hamid R. Arabnia, Khaled M. Rasheed, Wei-Peng Chen
Publikováno v:
2022 IEEE International Conference on Web Services (ICWS).
Generative Adversarial Networks (GANs) are machine learning methods that are used in many important and novel applications. For example, in imaging science, GANs are effectively utilized in generating image datasets, photographs of human faces, image
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86961e64b98260af4e5648e17f41ff10
http://arxiv.org/abs/2201.09152
http://arxiv.org/abs/2201.09152
Publikováno v:
IEEE Access, Vol 8, Pp 218386-218400 (2020)
Methodologies that utilize Deep Learning offer great potential for applications that automatically attempt to generate captions or descriptions about images and video frames. Image and video captioning are considered to be intellectually challenging
Publikováno v:
Transactions on Computational Science and Computational Intelligence ISBN: 9783030702953
Over the last decade, the use of Deep Learning in many applications produced results that are comparable to and in some cases surpassing human expert performance. The application domains include diagnosing diseases, finance, agriculture, search engin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21f613a5fc5791cf430f5d064e3da5c7
https://doi.org/10.1007/978-3-030-70296-0_2
https://doi.org/10.1007/978-3-030-70296-0_2
Publikováno v:
2020 International Conference on Computational Science and Computational Intelligence (CSCI).
Video Captioning is considered to be one of the most challenging problems in the field of computer vision. Video Captioning involves the combination of different deep learning models to perform object detection, action detection, and localization by
Publikováno v:
2019 International Conference on Computational Science and Computational Intelligence (CSCI).
Automatic image annotation, automatic image tagging, and image linguistic indexing functions use methodologies that significantly overlap. In this paper, we use the general term, image captioning, to refer to all forms of such functions. Image captio
Autor:
H.-B. Schüttler, Cristian Caranica, James F. Griffith, Thiab R. Taha, Jonathan Arnold, Ahmad Al-Omari
Publikováno v:
IEEE Access, Vol 6, Pp 54582-54594 (2018)
In the previous paper, we reconstructed the entire transcriptional network for all 2418 clock-associated genes in the model filamentous fungus, Neurospora crassa ( N. crassa ). Several authors have suggested that there is extensive post-transcription