Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Payberah, Amir H."'
Publikováno v:
2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)
Prompt-based language models have produced encouraging results in numerous applications, including Named Entity Recognition (NER) tasks. NER aims to identify entities in a sentence and provide their types. However, the strong performance of most avai
Externí odkaz:
http://arxiv.org/abs/2305.17951
Deep learning and remote sensing techniques have significantly advanced water monitoring abilities; however, the need for annotated data remains a challenge. This is particularly problematic in wetland detection, where water extent varies over time a
Externí odkaz:
http://arxiv.org/abs/2305.01698
Modern neural networks require long training to reach decent performance on massive datasets. One common approach to speed up training is model parallelization, where large neural networks are split across multiple devices. However, different device
Externí odkaz:
http://arxiv.org/abs/2201.09676
Publikováno v:
In International Journal of Applied Earth Observation and Geoinformation February 2024 126
Akademický článek
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Autor:
Nikolov, Nikolay, Dessalk, Yared Dejene, Khan, Akif Quddus, Soylu, Ahmet, Matskin, Mihhail, Payberah, Amir H., Roman, Dumitru
Publikováno v:
In Internet of Things December 2021 16
Autor:
Payberah, Amir H.
Peer-to-Peer (P2P) live media streaming is an emerging technology that reduces the barrier to stream live events over the Internet. However, providing a high quality media stream using P2P overlay networks is challenging and gives raise to a number o
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-24220
Autor:
Payberah, Amir H.
Media streaming over the Internet is becoming increasingly popular. Currently, most media is delivered using global content-delivery networks, providing a scalable and robust client-server model. However, content delivery infrastructures are expensiv
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-33287
Publikováno v:
Kamalian, Mahdieh Taherkordi, Amirhosein Payberah, Amir H. Ferreira, Paulo . FOGFLEET: Fog-Level Federated Transfer Learning for Adaptive Transport Mode Detection. Proceedings of the IEEE. 2024
Proceedings of the IEEE
Proceedings of the IEEE
Externí odkaz:
http://hdl.handle.net/10852/114456