Zobrazeno 1 - 10
of 99
pro vyhledávání: '"Chengfan Li"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2098-2114 (2024)
The fully supervised deep convolutional neural network (CNN) cannot detect the discriminant local information that is responsible for spatial transformations in high-resolution remote sensing images. To address the various types and missing labels of
Externí odkaz:
https://doaj.org/article/06b5c3a199fc4ed2be2d63713789522c
Autor:
Nianting Ju, Liangbing Nie, Yang Wang, Liying Hou, Chengfan Li, Xuehai Ding, Quanyong Luo, Chentian Shen
Publikováno v:
Frontiers in Endocrinology, Vol 14 (2023)
PurposeThe aim of this study was to predict standard uptake values (SUVs) from computed tomography (CT) images of patients with lung metastases from differentiated thyroid cancer (DTC-LM).MethodsWe proposed a novel SUVs prediction model using 18-laye
Externí odkaz:
https://doaj.org/article/b4aa5eec7a824a57bddb8fdaf967462f
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-19 (2021)
Abstract As a comprehensive utilization of pipeline resources, communication intelligent manhole cover (CIMC) can effectively real-time monitor communication manhole cover and protect the safety of communication pipeline. Due to the complex working e
Externí odkaz:
https://doaj.org/article/4551e1079c9547afa309ade862ee53e2
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2019, Iss 1, Pp 1-11 (2019)
Abstract Aiming at the sensitivity of fuzzy C-means (FCM) method to the initial clustering center and noise data, and the single feature being not able to segment the image effectively, this paper proposes a new image segmentation method based on fuz
Externí odkaz:
https://doaj.org/article/3161e2ce938241a6a1cbdd4c54d4ab11
Publikováno v:
IEEE Access, Vol 7, Pp 164507-164516 (2019)
The efficient classification of remote sensing images (RSIs) has become the key of remote sensing application. To tackle the high computational cost in the traditional classification method, in this paper we propose a new RSI classification method ba
Externí odkaz:
https://doaj.org/article/f114294c3c2746e995d5cfe8bb83ff2e
Publikováno v:
European Radiology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ccee5b624715e5229e26035694945c55
https://doi.org/10.1007/s00330-023-09687-w
https://doi.org/10.1007/s00330-023-09687-w
Publikováno v:
Security and Communication Networks, Vol 2022 (2022)
The intelligent information system constructed by the sensor web can monitor all kinds of sudden abnormal events, improve the ability of event discovery and rapid disposal, and promote the development of smart city and the construction of the Interne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0bad576551524c5d6f495326f82557f
https://doi.org/10.1155/2022/2578744
https://doi.org/10.1155/2022/2578744
Publikováno v:
Computer Modeling in Engineering & Sciences. 131:429-444
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91c037cf589b62b22705a32b39fe4fdd
https://doi.org/10.32604/cmes.2022.019202
https://doi.org/10.32604/cmes.2022.019202
Publikováno v:
International Journal of Digital Multimedia Broadcasting, Vol 2017 (2017)
We propose a novel approach for low-light image enhancement. Based on illumination-reflection model, the guided image filter is employed to extract the illumination component of the underlying image. Afterwards, we obtain the reflection component and
Externí odkaz:
https://doaj.org/article/fe50baf330c14dad9126f8d4b339f8d2
Publikováno v:
International Journal of Environmental Research and Public Health; Volume 19; Issue 10; Pages: 6322
The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated classification methods use electroencephalogram (EEG) signals for classification. These methods do not cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd58690b9c9119c185f050fc96d3a3d8