Zobrazeno 1 - 10
of 984
pro vyhledávání: '"Semantic context"'
Autor:
Fangmin Tan, Huaju Wang
Publikováno v:
IEEE Access, Vol 12, Pp 72023-72033 (2024)
Nowadays, machine translation has been a prevalent Internet application. But there still lacks mature intelligent algorithms to automatically evaluate quality of machine translation results. Considering the complexity inside machine intelligence-base
Externí odkaz:
https://doaj.org/article/8b9096b2abc5401ba5f4ebc2dc8c7f76
Publikováno v:
IEEE Access, Vol 12, Pp 55757-55767 (2024)
The contextual understanding ability in complex conversation scenarios has been a challenging issue, and existing methods mostly failed to possess such characteristics. To bridge such gap, this paper formulates a novel composite large language model
Externí odkaz:
https://doaj.org/article/cc28bec2e878408387b739fc97d0093d
Autor:
Peng Yang, Chunmei Li, Chengwu Fang, Shasha Kong, Yunpeng Jin, Kai Li, Haiyang Li, Xiangjie Huang, Yaosheng Han
Publikováno v:
IEEE Access, Vol 12, Pp 33544-33554 (2024)
In semantic segmentation, the efficient representation of multi-scale context is of paramount importance. Inspired by the remarkable performance of Vision Transformers (ViT) in image classification, subsequent researchers have proposed some Semantic
Externí odkaz:
https://doaj.org/article/58f48038d3584fb384bb6d3d3399481c
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 33, Iss 2, Pp 353-358 (2023)
Abstract—Traditional theoretical works on language processing systems define the syntax of a formal language as a set of rules of grammar, which a compiler can check, all other language aspects, which we can detect only in runtime. We call them "se
Externí odkaz:
https://doaj.org/article/f86c18c085214c4f82ecd9ca97560858
Publikováno v:
Applied Sciences, Vol 14, Iss 8, p 3442 (2024)
Neural machine translation (NMT) typically relies on a substantial number of bilingual parallel corpora for effective training. Mongolian, as a low-resource language, has relatively few parallel corpora, resulting in poor translation performance. Dat
Externí odkaz:
https://doaj.org/article/a8060c07584d4ac3a19efab744432ddd
Publikováno v:
Remote Sensing, Vol 15, Iss 17, p 4325 (2023)
Automatically extracting water bodies is a significant task in interpreting remote sensing images (RSIs). Convolutional neural networks (CNNs) have exhibited excellent performance in processing RSIs, which have been widely used for fine-grained extra
Externí odkaz:
https://doaj.org/article/03ece39866e74e418c97db6da785adff
Publikováno v:
Journal of Information and Organizational Sciences. 45(1):171-221
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=987614
Publikováno v:
Journal of Information and Organizational Sciences, Vol 45, Iss 1, Pp 171-221 (2021)
The traditional statistical approach in synonyms extraction is time-consuming. It is necessary to develop a new method to improve the efficiency and accuracy. This research presents a new method in synonyms extraction called Noun Based Distinctive Ve
Externí odkaz:
https://doaj.org/article/222a95f2bd984be688ed4b1106d521ba
Publikováno v:
IEEE Access, Vol 9, Pp 44610-44630 (2021)
In large-scale software development environments, defect reports are maintained through bug tracking systems (BTS) and analyzed by domain experts. Different users may create bug reports in a non-standard manner and may report a particular problem usi
Externí odkaz:
https://doaj.org/article/fed14915596f44d29fdae247abbbcbcf
Publikováno v:
Royal Society Open Science, Vol 9, Iss 3 (2022)
Some research suggests people are overconfident because of personality characteristics, lack of insight, or because overconfidence is beneficial in its own right. But other research fits with the possibility that fluent experience in the moment can r
Externí odkaz:
https://doaj.org/article/86f51aac57ed4d04b486cdf50d796d93