Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Jungang Xu"'
Publikováno v:
European Journal of Translational Myology (2024)
Muscle injuries, such as Achilles and quadriceps tendon ruptures, pose a significant challenge in elite sports, accounting for more than 30% of all sports-related injuries. Our primary goal is to investigate the MR imaging characteristics of tendon r
Externí odkaz:
https://doaj.org/article/15a5c59b5af14b8093036e9a2e77216c
Publikováno v:
Data Science and Engineering, Vol 2, Iss 4, Pp 316-327 (2017)
Abstract Clinical Decision Support (CDS) is widely seen as an information retrieval (IR) application in the medical domain. The goal of CDS is to help physicians find useful information from a collection of medical articles with respect to the given
Externí odkaz:
https://doaj.org/article/2f8811fcd0c14e6da15a7feb116e328e
Publikováno v:
Data Science Journal, Vol 6 (2007)
In this paper, a Bi-angle Model Management method (BiMM) is proposed to manage models in virtual reality research. One angle is based on the model itself, which includes the model, model scheme, and texture; another angle is based on the model sort -
Externí odkaz:
https://doaj.org/article/fbc515d2572f4e0285e3df7f10d5d5cf
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 24:331-340
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c11929179864ea7aa1e0784b228e5e89
https://doi.org/10.1109/tits.2022.3213413
https://doi.org/10.1109/tits.2022.3213413
Publikováno v:
Neural Networks. 158:111-120
Differentiable architecture search (DARTS) is one of the prevailing paradigms of neural architecture search (NAS) due to allowing efficient gradient-based optimization during the search phase. However, its poor stability and generalizability are into
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::222d5d23eda28d8fd9449047e078f79b
https://doi.org/10.1016/j.neunet.2022.11.015
https://doi.org/10.1016/j.neunet.2022.11.015
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:2585-2594
CNN-LSTM based architectures have played an important role in image captioning, but limited by the training efficiency and expression ability, researchers began to explore the CNN-Transformer based models and achieved great success. Meanwhile, almost
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::197f440b733e6e27efea62194e3e8011
https://doi.org/10.1609/aaai.v36i3.20160
https://doi.org/10.1609/aaai.v36i3.20160
Publikováno v:
Computational Intelligence and Neuroscience. 2022:1-12
With the development of artificial intelligence technology, an increasing number of researchers try to apply different machine learning and deep learning methods to quantitative trading fields to obtain more stable and efficient trading models. As a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::449e0ffb62e58bf8b34e1bfb6657b46c
https://doi.org/10.1155/2022/4743427
https://doi.org/10.1155/2022/4743427
Publikováno v:
Neurocomputing. 486:189-199
Neural architecture search (NAS) has made significant progress in recent years. However, existing methods usually search in a small-scale, well-designed architecture space, discover only one architecture in a single search, and hardly rework, severel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75d57140148963014250f162d0935611
https://doi.org/10.1016/j.neucom.2021.10.118
https://doi.org/10.1016/j.neucom.2021.10.118
Autor:
Pengfei Li, Jungang Xu
Publikováno v:
Wireless Communications and Mobile Computing. 2022:1-17
Due to the computer’s powerful data computing ability, more and more traditional investors pay attention to computer-based quantitative investment. Moreover, computer-based quantitative investment has gradually replaced some traditional investment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::798c0f941f84f2f7bcc841aff474ae41
https://doi.org/10.1155/2022/2695099
https://doi.org/10.1155/2022/2695099
Publikováno v:
Neurocomputing. 468:48-59
Object-level features from Faster R-CNN and attention mechanism have been used extensively in image captioning based on Encoder-Decoder frameworks. However, most existing methods feed the average pooling of object features as the global representatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd2d62844198ab9ced4baf80db851443
https://doi.org/10.1016/j.neucom.2021.10.014
https://doi.org/10.1016/j.neucom.2021.10.014