Zobrazeno 1 - 10
of 3 006
pro vyhledávání: '"Pre-training"'
Autor:
Emese Sükei, Elisabeth Rumetshofer, Niklas Schmidinger, Andreas Mayr, Ursula Schmidt-Erfurth, Günter Klambauer, Hrvoje Bogunović
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Self-supervised learning has become the cornerstone of building generalizable and transferable artificial intelligence systems in medical imaging. In particular, contrastive representation learning techniques trained on large multi-modal dat
Externí odkaz:
https://doaj.org/article/e132d120c2c040fc82016fb1d5498e81
Publikováno v:
Guangtongxin yanjiu, Pp 24004901-24004910 (2024)
【Objective】Compared to Electronic Packet Switching (EPS), Optical Circuit Switching (OCS) demonstrates advantages in latency, power consumption, cost, and stability. This study aims to explore feasible applications of OCS in the networking of tra
Externí odkaz:
https://doaj.org/article/d414340228524bdbb24e122a09a287cb
Autor:
Huanquan PAN, Jianqiao LIU, Bin GONG, Yiheng ZHU, Junhui BAI, Hu HUANG, Zhengbao FANG, Hongbin JING, Chen LIU, Tie KUANG, Yubo LAN, Tianzhi WANG, Tian XIE, Mingzhe CHENG, Bin QIN, Yujiang SHEN
Publikováno v:
Petroleum Exploration and Development, Vol 51, Iss 5, Pp 1357-1366 (2024)
A large language model (LLM) is constructed to address the sophisticated demands of data retrieval and analysis, detailed well profiling, computation of key technical indicators, and the solutions to complex problems in reservoir performance analysis
Externí odkaz:
https://doaj.org/article/60472ade71774d6d96b3357a3fc031b3
Publikováno v:
Geothermal Energy, Vol 12, Iss 1, Pp 1-25 (2024)
Abstract Deep learning has gained attention as a potentially powerful technique for modeling natural-state geothermal systems; however, its physical validity and prediction inaccuracy at extrapolation ranges are limiting. This study proposes the use
Externí odkaz:
https://doaj.org/article/98dec23e81004fc1a283719de796a275
Publikováno v:
Tongxin xuebao, Vol 45, Pp 101-114 (2024)
To address the limitations of current deep learning-based methods in extracting contract bytecode features and representing vulnerability semantics, as well as the shortcomings of the traditional graph neural networks in learning temporal information
Externí odkaz:
https://doaj.org/article/fcb835e5a8904ff286559029ffdd8fed
Autor:
He LIU, Yili REN, Xin LI, Yue DENG, Yongtao WANG, Qianwen CAO, Jinyang DU, Zhiwei LIN, Wenjie WANG
Publikováno v:
Petroleum Exploration and Development, Vol 51, Iss 4, Pp 1049-1065 (2024)
This article elucidates the concept of large model technology, summarizes the research status of large model technology both domestically and internationally, provides an overview of the application status of large models in vertical industries, outl
Externí odkaz:
https://doaj.org/article/8d586386df74454faacb406b7a55b66b
Publikováno v:
地质科技通报, Vol 43, Iss 4, Pp 224-234 (2024)
Objective With increasing difficulty in phosphate ore prospecting, there are an increasing number of geological exploration reports. The manual recognition of geological information related to phosphate rock mineralization in massive documents is tim
Externí odkaz:
https://doaj.org/article/becb4eb0096d4d35a708062b56e25fb4
Autor:
Yi-Lun Zhang, Wen-Tao Wang, Jia-Hui Guan, Deepak Kumar Jain, Tian-Yang Wang, Swalpa Kumar Roy
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-11 (2024)
Abstract Drug–target interactions is essential for advancing pharmaceuticals. Traditional drug–target interaction studies rely on labor-intensive laboratory techniques. Still, recent advancements in computing power have elevated the importance of
Externí odkaz:
https://doaj.org/article/b3a4687435f4481e90167f57a38d035e
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract The early screening of depression is highly beneficial for patients to obtain better diagnosis and treatment. While the effectiveness of utilizing voice data for depression detection has been demonstrated, the issue of insufficient dataset s
Externí odkaz:
https://doaj.org/article/81d495a9cda74eafa45e74f4b8e90b5c
Autor:
Feng-ao Wang, Zhenfeng Zhuang, Feng Gao, Ruikun He, Shaoting Zhang, Liansheng Wang, Junwei Liu, Yixue Li
Publikováno v:
Genome Biology, Vol 25, Iss 1, Pp 1-24 (2024)
Abstract Cancer is a complex disease composing systemic alterations in multiple scales. In this study, we develop the Tumor Multi-Omics pre-trained Network (TMO-Net) that integrates multi-omics pan-cancer datasets for model pre-training, facilitating
Externí odkaz:
https://doaj.org/article/0d10d2ea456e4903bb23f8991e72ab2a