Zobrazeno 1 - 10
of 167
pro vyhledávání: '"deep convolution neural networks"'
Publikováno v:
IEEE Access, Vol 12, Pp 142071-142082 (2024)
The Pediatric Intensive Care Unit (PICU) receives critically ill patients with shortness of breath and poor body oxygenation. Various respiratory parameters, such as respiratory rate, oxygen saturation level, and heart rate, are continuously monitore
Externí odkaz:
https://doaj.org/article/8a1f992fad384138b6aebb2c98ab0253
Autor:
Wantai Chen, Xiaofeng Li
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 8043-8057 (2024)
Efficient monitoring of marine aquaculture zones (MAZs) is crucial for facilitating coastal resource management. To achieve this, we developed a specialized deep convolutional neural network tailored for extracting MAZs from synthetic aperture radar
Externí odkaz:
https://doaj.org/article/f37a32930c9a4cb69ef3062337d41b6b
Publikováno v:
Computation, Vol 12, Iss 4, p 72 (2024)
Communication among hard-of-hearing individuals presents challenges, and to facilitate communication, sign language is preferred. Many people in the deaf and hard-of-hearing communities struggle to understand sign language due to their lack of sign-m
Externí odkaz:
https://doaj.org/article/a8f7f362a8b74f4baa10e9901234f588
Akademický článek
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Akademický článek
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Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 6943-6956 (2022)
Semantic segmentation of high-resolution aerial images is a challenging task on account of interclass homogeneity and intraclass heterogeneity of land cover. Recent works have sought to mitigate this issue by exploiting pixelwise global contextual in
Externí odkaz:
https://doaj.org/article/b81691d2294d4557b2f481e0b015bdb4
Publikováno v:
Xibei Gongye Daxue Xuebao, Vol 39, Iss 5, Pp 1122-1129 (2021)
Special scene classification and identification tasks are not easily fulfilled to obtain samples, which results in a shortage of samples. The focus of current researches lies in how to use source domain data (or auxiliary domain data) to build domain
Externí odkaz:
https://doaj.org/article/42e9187288c94bbe94948ffec2634e00
Publikováno v:
IEEE Access, Vol 9, Pp 27959-27970 (2021)
Deep learning is thought of as a promising mean to identify maize diseases. However, the drawback of deep learning is the huge sample data and low accuracy. In this paper, we proposed a multi-scale convolutional global pooling neural network to impro
Externí odkaz:
https://doaj.org/article/24b28e9967654e7285df81ed4a33135e
Publikováno v:
IEEE Access, Vol 9, Pp 36819-36826 (2021)
Cost function is one of the most important topics in face recognition. Classic methods based on anchor-positive-negative sample pairs directly or indirectly have been proved to be effective. Taking advantage of information from sample pair with label
Externí odkaz:
https://doaj.org/article/249184cf355941df8f1dabf60b8bab19
Publikováno v:
IEEE Access, Vol 8, Pp 29729-29741 (2020)
In large field of view for open country, the real-time detection and identification of moving objects with high accuracy is a very challenging work due to the excessive amount of data. This paper proposes a novel framework that consists of a coarse-g
Externí odkaz:
https://doaj.org/article/38a0cc48f6404bb78e32f6e0843c77ec