Zobrazeno 1 - 10
of 733
pro vyhledávání: '"generative adversarial networks (GAN)"'
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 6, Pp 1579-1589 (2024)
In the Internet era, recommender systems become more and more significant in the daily life. The combination of generative adversarial networks (GAN) and recommended algorithm provides new opportunities for the development of this field. In previous
Externí odkaz:
https://doaj.org/article/2d191e9dbc1c4f08bef0915ece6c0248
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 4, Pp 534-544 (2024)
Characteristic viscosity is a key indicator of the quality of polyester melts, whose accurate prediction can help to identify potential quality problems of polyester melts in advance, adjust the process parameters in time and reduce enterprise losses
Externí odkaz:
https://doaj.org/article/c7e3f67d88bd4209a3d4c36c7e52d8ce
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The number of patents increases quickly, while more and more low-quality patents are emerging. It’s important to identify high-quality patents from massive data quickly and accurately for organizational R&D decision-making and patent layou
Externí odkaz:
https://doaj.org/article/a3799e821f66442ab39771228c8cbd9c
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 1, Pp 244-251 (2024)
Face images distributed widely on social networks are vulnerable to inferring sensitive information by unauthorized automatic identification systems, which poses a threat to user privacy. To protect face privacy, several methods have been proposed to
Externí odkaz:
https://doaj.org/article/170018f283de47858ad319a4cc56b9f6
Publikováno v:
IEEE Access, Vol 12, Pp 32308-32319 (2024)
We designed a generative adversarial network and an attention network to solve the brainwave emotion-classification problem. Using spatial attention and channel attention superposition to normalize and enhance the raw EEG data, we effectively solved
Externí odkaz:
https://doaj.org/article/403a098b326640789dc7361dbde4b1fa
Publikováno v:
IEEE Access, Vol 12, Pp 26787-26799 (2024)
The richness of textures and semantic information from RGB images can be supplemented in computer vision by the robustness of thermal images to light variations and weather artifacts. While many models rely on inputs from one sensor modality, image t
Externí odkaz:
https://doaj.org/article/ab3b11eb48ff44df8f768dd788167727
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3211-3225 (2024)
Collecting large-scene synthetic aperture radar (SAR) images with targets of interest (TOI) has been a challenging task. To embed TOI slices into measured large scenes can be a good solution. Current methods for SAR TOI slice generation are mainly ba
Externí odkaz:
https://doaj.org/article/88a8fff1b0db48949fb4fc66499c131d
Publikováno v:
电力工程技术, Vol 43, Iss 1, Pp 229-237 (2024)
In the novel power system of urban grid, the multiple resources increase and the data collection becomes more difficult, which lead to a higher random missing data rate. It is difficult to meet the demand for refined analysis and decision making. For
Externí odkaz:
https://doaj.org/article/17f7d7d45fe64a0a9385dd3dbb4b1cda
Publikováno v:
电力工程技术, Vol 43, Iss 1, Pp 157-164 (2024)
Power system planning, load forecasting, and energy utilization analysis are significantly impacted by power load anomalies, necessitating prompt detection and identification. Firstly, the abnormal classification, causes, and characteristics of power
Externí odkaz:
https://doaj.org/article/fe30ed0dacbc40bd9179a7c9d7099a55
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 282-297 (2024)
In this article, the vegetative drought prediction employing Deep Learning (DL) models is designed, incorporating rainfall data and NOAA satellite-data-derived Vegetation Health Index (VHI) values spanning 1981–2022. Correspondingly, two DL-oriente
Externí odkaz:
https://doaj.org/article/78f91b1f953e4856b35e4535f20ad9f7