Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Shuailiang Zhang"'
Publikováno v:
Applied Sciences, Vol 13, Iss 21, p 11886 (2023)
Aiming at the problem of being unable to meet some high computing power, high-precision applications due to the limited capacity of underwater sensor nodes, and the difficulty of low computation power, in this paper, we introduce the edge servers, kn
Externí odkaz:
https://doaj.org/article/6d7196a9b44a4330bac8b0f5922bc2fd
Publikováno v:
IEEE Access, Vol 8, Pp 48285-48298 (2020)
Underwater acoustic networks (UANs) have emerged as a new wireless sensor network structure widely used in many applications. Sensor nodes are usually placed in a hostile and unattended underwater environment to gather information with limited resour
Externí odkaz:
https://doaj.org/article/2ce402895ee94da6bcfa316d8c6a2ca9
Publikováno v:
Wireless Networks.
Publikováno v:
IEEE Access, Vol 8, Pp 48285-48298 (2020)
Underwater acoustic networks (UANs) have emerged as a new wireless sensor network structure widely used in many applications. Sensor nodes are usually placed in a hostile and unattended underwater environment to gather information with limited resour
Publikováno v:
Security and Communication Networks, Vol 2021 (2021)
As the most popular way of communication technology at the moment, wireless sensor networks have been widely concerned by academia and industry and plays an important role in military, agriculture, medicine, and other fields. Identity authentication
Publikováno v:
EMNLP (Findings)
In this paper, we present Linguistics Informed Multi-Task BERT (LIMIT-BERT) for learning language representations across multiple linguistics tasks by Multi-Task Learning. LIMIT-BERT includes five key linguistics tasks: Part-Of-Speech (POS) tags, con
Publikováno v:
AAAI
Multi-choice reading comprehension is a challenging task to select an answer from a set of candidate options when given passage and question. Previous approaches usually only calculate question-aware passage representation and ignore passage-aware qu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c8ebef64cbb58abaae14ed01c9cf9db
Publikováno v:
AAAI
The latest work on language representations carefully integrates contextualized features into language model training, which enables a series of success especially in various machine reading comprehension and natural language inference tasks. However
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a91fc837aaf6ef4df17982cf6e3b6969