Zobrazeno 1 - 10
of 174
pro vyhledávání: '"Yunhui SHI"'
Publikováno v:
Sensors, Vol 24, Iss 19, p 6184 (2024)
Recently, deep unfolding network methods have significantly progressed in hyperspectral snapshot compressive imaging. Many approaches directly employ Transformer models to boost the feature representation capabilities of algorithms. However, they oft
Externí odkaz:
https://doaj.org/article/c30c40f0eb564b7c86eb429b2ebc62ce
Publikováno v:
Sensors, Vol 24, Iss 16, p 5439 (2024)
The surge in image data has significantly increased the pressure on storage and transmission, posing new challenges for image compression technology. The structural texture of an image implies its statistical characteristics, which is effective for i
Externí odkaz:
https://doaj.org/article/033eff522ed44357934a56ba33645e63
Publikováno v:
IEEE Access, Vol 11, Pp 34510-34528 (2023)
The power sector bears significant responsibility for achieving carbon neutrality. Low-carbon, high-flexibility generation technologies are pivotal in the generation mix of the foreseeable future. In this paper, a mixed-integer operation model of com
Externí odkaz:
https://doaj.org/article/50fee108a180441bb916c3c54d3735fd
Publikováno v:
Agriculture, Vol 14, Iss 2, p 208 (2024)
During the growth stage of soybean seedlings, it is crucial to quickly and precisely identify them for emergence rate assessment and field management. Traditional manual counting methods have some limitations in scenarios with large-scale and high-ef
Externí odkaz:
https://doaj.org/article/25da657cd8e64e38baed66d02cb1f3a7
Autor:
He Li, Changle Guo, Zishang Yang, Jiajun Chai, Yunhui Shi, Jiawei Liu, Kaifei Zhang, Daoqi Liu, Yufei Xu
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Deep learning techniques have made great progress in the field of target detection in recent years, making it possible to accurately identify plants in complex environments in agricultural fields. This project combines deep learning algorithms with s
Externí odkaz:
https://doaj.org/article/cd0d4c4940af4803af27c80601238ce6
Publikováno v:
Mathematics, Vol 11, Iss 11, p 2557 (2023)
A multi-stage robust real-time economic dispatch model (MRRTD) for power systems is proposed in this paper. The MRRTD takes the dynamic form of multi-stage robust optimization as the framework to naturally simulate the operation of equipment that is
Externí odkaz:
https://doaj.org/article/1a57e893a17c43dabe51e4924f77c395
Publikováno v:
发电技术, Vol 41, Iss 2, Pp 118-125 (2020)
Uncertainties in renewable energy and loads bring challenges to the operation of integrated energy system (IES). Firstly, the general model of the industrial park's IES was established based on the linear energy hub. Then a two-stage economic dispatc
Externí odkaz:
https://doaj.org/article/a284f37d2e0d4922bf8b31480afe8a13
Autor:
Yunhui SHI, Chuangxin GUO
Publikováno v:
发电技术, Vol 41, Iss 1, Pp 56-63 (2020)
In order to solve the risk problem brought by uncertainties of supply and demand in integrated energy system (IES), an optimal dispatch model of IES with energy storage considering operational risk was proposed. In the objective function, the cost of
Externí odkaz:
https://doaj.org/article/4ec1c7df8fda4e889c6d712f905f5539
Publikováno v:
Applied Sciences, Vol 10, Iss 8, p 2891 (2020)
The sparsity of images in a certain transform domain or dictionary has been exploited in many image processing applications. Both classic transforms and sparsifying transforms reconstruct images by a linear combination of a small basis of the transfo
Externí odkaz:
https://doaj.org/article/9cc19be78e3b4d8189bfb63d2fe7e3f0
Publikováno v:
Applied Sciences, Vol 10, Iss 5, p 1771 (2020)
Overcomplete representation is attracting interest in image restoration due to its potential to generate sparse representations of signals. However, the problem of seeking sparse representation must be unstable in the presence of noise. Restricted Is
Externí odkaz:
https://doaj.org/article/6469215f8ff847f1b04233bd28ef9793