Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Yun Tie"'
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 8, Iss 2, Pp 285-287 (2023)
Externí odkaz:
https://doaj.org/article/b19a0c95f53942eea5176dfdae4c1441
Autor:
Cong Jin, Tao Wang, Xiaobing Li, Chu Jie Jiessie Tie, Yun Tie, Shan Liu, Ming Yan, Yongzhi Li, Junxian Wang, Shenze Huang
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 7, Iss 3, Pp 369-380 (2022)
Abstract This study proposes a new generation network based on transformers and guided by the music theory to produce high‐quality music work. In this study, the decoding block of the transformer is used to learn the internal information of single
Externí odkaz:
https://doaj.org/article/b61db608fbbe41ef97226390a58a3499
Publikováno v:
IEEE Access, Vol 6, Pp 28097-28107 (2018)
Semi-supervised learning (SSL) utilizes limited labeled data and plenty of unlabeled data, and it has attracted attentions for its improved learning performance. However, recent studies have indicated that using unlabeled data, in some cases, could d
Externí odkaz:
https://doaj.org/article/a23d984cb4e84c6492389dfa632a11bd
Publikováno v:
Interdisciplinary Sciences: Computational Life Sciences. 15:217-230
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7554980c2de0e5c20f803f2ec81b4a3
https://doi.org/10.1007/s12539-023-00554-2
https://doi.org/10.1007/s12539-023-00554-2
Publikováno v:
Wireless Communications and Mobile Computing. 2022:1-7
Multitrack music generation technology is becoming more and more mature, but the existing generation technology cannot reach the desired effect in terms of harmony and matching degree, and most of the generated music does not conform to the music the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::940cb6c6cadf03f087570a8885ac58d9
https://doi.org/10.1155/2022/5845689
https://doi.org/10.1155/2022/5845689
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery. 17:1059-1068
Lung cancer usually presents as pulmonary nodules on early diagnostic images, and accurately estimating the malignancy of pulmonary nodules is crucial to the prevention and diagnosis of lung cancer. Recently, deep learning algorithms based on convolu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c37bcc3516e68331fb2e2212a200b72c
https://doi.org/10.1007/s11548-022-02576-5
https://doi.org/10.1007/s11548-022-02576-5
Objective: To overcome the phenomenon of “dimensionality curse” and class imbalance existing in biomolecule data and take full advantage of it to realize pan-cancer prediction and biomarker identification. Methods: We collected a total of 6133 sa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a2665c214add4cefcc44d8af60fdb9d
https://doi.org/10.21203/rs.3.rs-2480639/v1
https://doi.org/10.21203/rs.3.rs-2480639/v1
Publikováno v:
Neural Information Processing ISBN: 9783031301100
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1679f339b05d99edd751028994eb61d5
https://doi.org/10.1007/978-3-031-30111-7_6
https://doi.org/10.1007/978-3-031-30111-7_6
Publikováno v:
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7904d60d45630f2fa9ec4d9a72f25b67
https://doi.org/10.1109/bibm55620.2022.9995432
https://doi.org/10.1109/bibm55620.2022.9995432