Zobrazeno 1 - 10
of 18
pro vyhledávání: '"YuBo Zheng"'
Autor:
Mu Shen, Hongchuan Niu, Qing Xia, Bing Zou, Yubo Zheng, Yuanli Zhao, Lei Li, Xianzeng Liu, Lin Zhang
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 981-990 (2023)
High-frequency activity (HFA) in intracranial electroencephalography recordings are diagnostic biomarkers for refractory epilepsy. Clinical utilities based on HFA have been extensively examined. HFA often exhibits different spatial patterns correspon
Externí odkaz:
https://doaj.org/article/52a1ee2d76ab40829044aaacb7ebc9ff
Autor:
Zhejun Zhang, Yingqi Zhu, Yubo Zheng, Yingying Luo, Hengyi Shao, Shaoting Guo, Liang Dong, Lin Zhang, Lei Li
Publikováno v:
Applied Sciences, Vol 14, Iss 2, p 875 (2024)
(1) Background: Information overload challenges decision-making in the Industry 4.0 era. While Natural Language Processing (NLP), especially Automatic Text Summarization (ATS), offers solutions, issues with factual accuracy persist. This research bri
Externí odkaz:
https://doaj.org/article/e0cfe68d279a4224abb96edb0e41194c
Publikováno v:
Agronomy, Vol 13, Iss 8, p 2026 (2023)
The health status of Quaternary red soil is a comprehensive reflection of the production and ecological service functions, which directly affects agricultural productivity and ecosystem sustainability. Based on the Cornell Soil Health Assessment (CAS
Externí odkaz:
https://doaj.org/article/8311eb4ca4684bb29c8149cdaf2d9ca6
Publikováno v:
Applied Sciences, Vol 13, Iss 13, p 7908 (2023)
Contrastive learning, as an unsupervised technique, has emerged as a prominent method in time series representation learning tasks, serving as a viable solution to the scarcity of annotated data. However, the application of data augmentation methods
Externí odkaz:
https://doaj.org/article/9e6686a50fdd49fa93524782d3085779
Publikováno v:
Applied Sciences; Volume 13; Issue 13; Pages: 7908
Contrastive learning, as an unsupervised technique, has emerged as a prominent method in time series representation learning tasks, serving as a viable solution to the scarcity of annotated data. However, the application of data augmentation methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::3aaf1fe2471c7af366cfcab5af8757a6
Publikováno v:
2023 11th International IEEE/EMBS Conference on Neural Engineering (NER).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1026ebc69c95f2135ffa6ac92535feb8
https://doi.org/10.1109/ner52421.2023.10123742
https://doi.org/10.1109/ner52421.2023.10123742
Publikováno v:
Future Generation Computer Systems. 125:32-40
The FIDO2 protocol allows users to perform online authentication by setting a public key and avoids the shortcomings of the traditional password authentication mechanism in terms of security. During transaction confirmation with the FIDO2 protocol, u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d37be9679ce41c609807ba96134f0d59
https://doi.org/10.1016/j.future.2021.06.034
https://doi.org/10.1016/j.future.2021.06.034
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Computer Security – ESORICS 2022 ISBN: 9783031171451
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Security – ESORICS 2022
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Security – ESORICS 2022
Many practical secure systems have been designed to prevent real-world attacks via maximizing the attacking cost so as to reduce attack intentions. Inspired by this philosophy, we propose a new concept named delay encryption with keyword search (DEKS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::484f6e9609dabe1b11670a6648a5e824
https://doi.org/10.1007/978-3-031-17146-8_5
https://doi.org/10.1007/978-3-031-17146-8_5
Publikováno v:
Pattern Recognition and Computer Vision ISBN: 9783030880033
PRCV (1)
PRCV (1)
The level of safety in power grid construction has been improved by Computer Vision (CV) recently with deep Convolutional Neural Networks (CNN). However, due to environmental complexity and risk behaviors diversity, the current detection algorithms s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72e4e91205a317d2b387a2062d23392f
https://doi.org/10.1007/978-3-030-88004-0_26
https://doi.org/10.1007/978-3-030-88004-0_26