Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Fusheng Jin"'
Publikováno v:
Applied Sciences, Vol 13, Iss 1, p 91 (2022)
Deep learning technology has been widely applied in emitter identification. With the deepening research, the problem of emitter identification under the few-shots condition has become a frontier research direction. As a special communication signal,
Externí odkaz:
https://doaj.org/article/6cc10c9982c3402f9eb3769387e350e2
Publikováno v:
Remote Sensing, Vol 13, Iss 9, p 1764 (2021)
Depth estimation can provide tremendous help for object detection, localization, path planning, etc. However, the existing methods based on deep learning have high requirements on computing power and often cannot be directly applied to autonomous mov
Externí odkaz:
https://doaj.org/article/98b3d44f512049b0a513b80747c6b0da
Publikováno v:
Future Generation Computer Systems. 142:292-300
Publikováno v:
International Journal of Software & Informatics; 2023, Vol. 13 Issue 4, p379-397, 19p
Publikováno v:
Information Sciences. 579:814-831
In recent years, the Internet of vehicles (IoV) technology becomes a research hotspot . However, it also becomes a hotbed for malicious attacks . In the IoV, frequent data transmission and complex connections among numerous different nodes increase t
Publikováno v:
Neural Computing and Applications. 35:3587-3595
Active learning is an effective technique to reduce the cost of labeling data by selecting the most beneficial samples. Most existing active learning methods use linear models to select the most representative points to approximate other points. Howe
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
International Journal of Data Warehousing and Mining. 14:67-89
Subgraph matching, which belongs to NP-hard, faces significant challenges on a large scale graph with billions of nodes, and existing methods are usually confronted with greater challenges from both stability and efficiency. In this article, a subgra
Autor:
Dengfeng Zhou, Li Daiyuan, Liu Menglei, Zhe Wang, Huige Wei, Qinglong Jiang, Zhong Xianshuai, Fusheng Jin, Dapeng Cui
Publikováno v:
ES Food & Agroforestry.
Publikováno v:
Knowledge Science, Engineering and Management ISBN: 9783030551292
KSEM (1)
KSEM (1)
Depth estimation from a single image plays an important role in computer vision. Using semantic information for depth estimation becomes a research hotspot. The traditional neural network-based semantic method only divides the image according to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab35b96c01980f33855a9bd6881cfa9b
https://doi.org/10.1007/978-3-030-55130-8_4
https://doi.org/10.1007/978-3-030-55130-8_4