Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Tingyao Jiang"'
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-18 (2024)
Abstract Insulator defect detection is a critical aspect of grid inspection in reality, yet it faces intricate environmental challenges, such as slow detection speed and low accuracy. To address this issue, we propose a YOLOv8-based insulator defect
Externí odkaz:
https://doaj.org/article/669b213b11fb405299c8b580207072d7
Publikováno v:
IEEE Access, Vol 12, Pp 54191-54201 (2024)
In today’s network environments, vulnerable to cyber threats such as hackers and viruses, intrusion detection technology is considered the most effective means of detection and defense. Deep neural networks are commonly used in intrusion detection
Externí odkaz:
https://doaj.org/article/97cedad65bfb4bfb97ebeb5ab42fd617
Autor:
Tingyao Jiang, Shuo Chen
Publikováno v:
Applied Sciences, Vol 14, Iss 5, p 1941 (2024)
In response to the shortcomings of traditional pest detection methods, such as inadequate accuracy and slow detection speeds, a lightweight forestry pest image recognition model based on an improved YOLOv8 architecture is proposed. Initially, given t
Externí odkaz:
https://doaj.org/article/23f8c7eb8fea45c2901fca612c5b7f8d
Autor:
Yunqin Liu, Tingyao Jiang
Publikováno v:
Environmental Research Communications, Vol 6, Iss 9, p 095027 (2024)
Digital economy has become an important engine for promoting green development.The existing literature mainly analyzed the impact of digital economy on green development, but rarely examines the coordinated development relationship between the two. T
Externí odkaz:
https://doaj.org/article/613c8bbd3aa0443a933d12428a04d228
Publikováno v:
Applied Sciences, Vol 13, Iss 21, p 11940 (2023)
The safety of transmission lines is essential for ensuring the secure and dependable operation of the power grid. However, the harm caused by birds to transmission lines poses a direct threat to their safe operation. The main challenges in detecting
Externí odkaz:
https://doaj.org/article/4dba98aab11c4c1b8751c416c60389c4
Publikováno v:
Information, Vol 14, Iss 7, p 416 (2023)
Sentence-level sentiment analysis, as a research direction in natural language processing, has been widely used in various fields. In order to address the problem that syntactic features were neglected in previous studies on sentence-level sentiment
Externí odkaz:
https://doaj.org/article/569f9264a0a74066b49636087b0b0223
Publikováno v:
Information, Vol 14, Iss 3, p 185 (2023)
Aspect-based sentiment analysis is a fine-grained sentiment analysis that focuses on the sentiment polarity of different aspects of text, and most current research methods use a combination of dependent syntactic analysis and graphical neural network
Externí odkaz:
https://doaj.org/article/e5d7b298beab4b9994d934fa9e2e350d
Publikováno v:
IEEE Access, Vol 8, Pp 171218-171239 (2020)
An automatic thresholding method based on Shannon entropy difference and dynamic synergic entropy is proposed to select a reasonable threshold from the gray level image with a unimodal, bimodal, multimodal, or peakless gray level histogram. Firstly,
Externí odkaz:
https://doaj.org/article/1d1c2128c0e34ad29c070c67d95fb2b9
Autor:
Tingyao Jiang1, Yunqin Liu2,3 yunqin0626@126.com
Publikováno v:
Polish Journal of Environmental Studies. 2024, Vol. 33 Issue 5, p5735-5746. 12p.
Publikováno v:
Electronics; Volume 11; Issue 16; Pages: 2494
To improve the accuracy of the You Only Look Once v5s (YOLOv5s) algorithm for object detection, this paper proposes an improved YOLOv5s algorithm, CBAM-YOLOv5s, which introduces an attention mechanism. A convolutional block attention module (CBAM) is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34586da9c80711c095ee62404e2c3b32