Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Yuxia Lei"'
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7524 (2024)
Aspect-level sentiment classification (ALSC) struggles with correctly trapping the aspects and corresponding sentiment polarity of a statement. Recently, several works have combined the syntactic structure and semantic information of sentences for mo
Externí odkaz:
https://doaj.org/article/bec5be366c5045198da541149f85cbd2
Autor:
Yuxia Lei, Zhongqiang Wu
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2020, Iss 1, Pp 1-13 (2020)
Abstract This paper presents a statistical feature approach in fully convolutional time series classification (TSC), which is aimed at improving the accuracy and efficiency of TSC. This method is based on fully convolutional neural networks (FCN), an
Externí odkaz:
https://doaj.org/article/0487169a24484f2fb0a098766e0d226f
Publikováno v:
Peer-to-Peer Networking and Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e11f6cf58f661d832c01248468dc9bbe
https://doi.org/10.1007/s12083-023-01490-0
https://doi.org/10.1007/s12083-023-01490-0
Autor:
Zhongqiang Wu, Yuxia Lei
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2020, Iss 1, Pp 1-13 (2020)
This paper presents a statistical feature approach in fully convolutional time series classification (TSC), which is aimed at improving the accuracy and efficiency of TSC. This method is based on fully convolutional neural networks (FCN), and there a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::504056595fa70bce6458119c12d007f8
http://link.springer.com/article/10.1186/s13638-020-1661-4
http://link.springer.com/article/10.1186/s13638-020-1661-4
Publikováno v:
Scientific Programming.
In the design of wireless sensor networks (WSNs), it is important to reduce energy consumption and extend the service life of the sensors. Selecting one of the minimum sensor combinations (MSCs) that can monitor all areas, while the other MSCs are as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3adbc938da687b98e0f4c4f992a2180
Sentiment analysis based on statistics has rapidly developed in deep-learning. Bilateral attention neural network (BANN), especially Bidirectional Encoder Representations from Transformers (BERT), has reached high accuracy. However, with the increase
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10aa58126731fa12b9278db772539a00
https://doi.org/10.21203/rs.3.rs-181676/v1
https://doi.org/10.21203/rs.3.rs-181676/v1
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030699918
With the popularity of large-scale corpora, statistics-based models have become mainstream model in Natural Language Processing (NLP). The Bidirectional Encoder Representations from Transformers (BERT), as one of those models, has achieved excellent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c8c9deff67c002a90b57cbabe71a9fb5
https://doi.org/10.1007/978-3-030-69992-5_3
https://doi.org/10.1007/978-3-030-69992-5_3
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030699918
Microarray gene technology solves the problem of obtaining gene expression data. It is a significant part for current research to obtain effective information from omics genes quickly. Feature selection is an important step of data preprocessing, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::154759f745f6931312dc1afc9415fd74
https://doi.org/10.1007/978-3-030-69992-5_4
https://doi.org/10.1007/978-3-030-69992-5_4
Publikováno v:
ICESS
The neural network of bilateral attention, especially Bidirectional Encoder Representations from Transformers (BERT), has achieved good results since its appearance, and has obtained high scores in various tasks of Natural Language Processing (NLP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::172ad9d539e330ccbcfb1b213a7b6686
https://doi.org/10.1109/icess49830.2020.9301570
https://doi.org/10.1109/icess49830.2020.9301570
Autor:
Yuxia Lei, Linlin Zhang
Publikováno v:
Internet Technology Letters. 4
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d666e229d3e15853adbd560406eb768e
https://doi.org/10.1002/itl2.196
https://doi.org/10.1002/itl2.196