Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Tamam Alsarhan"'
Publikováno v:
IEEE Access, Vol 12, Pp 162608-162621 (2024)
Recently, there has been a surge of interest in utilizing Graph Convolutional Networks (GCNs) for skeleton- based action recognition, where learning effective representations of the skeletal graph is of paramount importance for attaining success in t
Externí odkaz:
https://doaj.org/article/4ac8f521471c43d2a2ac3982276a2ba8
Autor:
Mohammad Alshinwan, Ahmed Younes Shdefat, Nour Mostafa, Abdullah A.M AlSokkar, Tamam Alsarhan, Dmaithan Almajali
Publikováno v:
International Journal of Data and Network Science, Vol 7, Iss 2, Pp 941-956 (2023)
Blockchain technology is one of the crypto-currency technologies that has received a lot of attention. It has also found use in various applications, including the Internet of Things (IoT) and Cloud computing. Nonetheless, Blockchain has a significa
Externí odkaz:
https://doaj.org/article/3911642e3d3f4b9e9c5ac9c6d5b6aa2e
Publikováno v:
2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18497c32f52a6b92940a0125f416d5ac
https://doi.org/10.1109/csnt57126.2023.10134714
https://doi.org/10.1109/csnt57126.2023.10134714
Autor:
Tamam Alsarhan, Osama Harfoushi, Ahmed Younes Shdefat, Nour Mostafa, Mohammad Alshinwan, Ahmad Ali
Publikováno v:
Electronics
Volume 12
Issue 4
Pages: 879
Volume 12
Issue 4
Pages: 879
Lately, skeleton-based action recognition has drawn remarkable attention to graph convolutional networks (GCNs). Recent methods have focused on graph learning because graph topology is the key to GCNs. We propose to align graph learning on the channe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99b2e30c3a45b50cab985e59612118cb
Autor:
Tamam Alsarhan, Hongtao Lu, Mohammad Al-Zinati, Mahmoud Al-Ayyoub, Luay Alawneh, Yaser Jararweh
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 12:10565-10580
Human activity recognition is concerned with detecting different types of human movements and actions using data gathered from various types of sensors. Deep learning approaches, when applied on time series data, offer promising results over intensiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1b52b1b7850bc5da68d98c167656133
https://doi.org/10.1007/s12652-020-02865-4
https://doi.org/10.1007/s12652-020-02865-4
Autor:
Tamam Alsarhan
Publikováno v:
The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success ISBN: 9783030627959
Artificial Intelligence (AI) is the broad science that concerned with teaching machines to “think” or perform tasks like humans. Recently, AI is driving the progress in various up-to-date applications in natural language processing, computer visi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d5db9ddd214e4bdf8339488794f809c
https://doi.org/10.1007/978-3-030-62796-6_27
https://doi.org/10.1007/978-3-030-62796-6_27
Autor:
Hongtao Lu, Tamam Alsarhan
Publikováno v:
PRICAI 2021: Trends in Artificial Intelligence ISBN: 9783030893699
PRICAI (3)
PRICAI (3)
Massive progress for vision-based action recognition has been made in the last few years, owing to the advancement of deep convolutional neural networks (CNNs). In contrast with 2D CNN-based approaches, 3D CNN-based approaches can effectively capture
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::196781665f65e8d5fb5cd693fc963143
https://doi.org/10.1007/978-3-030-89370-5_11
https://doi.org/10.1007/978-3-030-89370-5_11
Publikováno v:
Computer Vision and Image Understanding. 216:103348
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d006e1fca612123d1a754e5224df77dd
https://doi.org/10.1016/j.cviu.2021.103348
https://doi.org/10.1016/j.cviu.2021.103348
Publikováno v:
Image and Vision Computing. 113:104261
Learning depth from a single image is a challenging task in computer vision. Many recent works on monocular depth estimation explore increasingly large convolutional neural networks to learn monocular cues implicitly. Such methods may fail to general
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b66b2274379a816b882c662686486c3
https://doi.org/10.1016/j.imavis.2021.104261
https://doi.org/10.1016/j.imavis.2021.104261
Publikováno v:
2019 IEEE SENSORS.
Human activity recognition aims to detect the type of human movement based on sensor data gathered during human activity. Time series classification using deep learning approaches offers opportunities to avoid intensive handcrafted feature extraction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2c359c571ece139e0b98504409965e05
https://doi.org/10.1109/sensors43011.2019.8956560
https://doi.org/10.1109/sensors43011.2019.8956560