Zobrazeno 1 - 10
of 612
pro vyhledávání: '"Xingzhao LIU"'
Publikováno v:
工程科学学报, Vol 46, Iss 3, Pp 458-469 (2024)
Due to the petrochemical energy and environmental challenges, clean and renewable energy sources have attracted the extensive attention. Furthermore, composite phase change materials with high photothermal conversion and thermal energy storage effici
Externí odkaz:
https://doaj.org/article/8b6d6bba6c2240858351da1584439b56
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11794-11808 (2024)
Semisupervised change detection (CD) methods have garnered increasing attention due to their capacity to alleviate the dependency of fully-supervised methods on a large number of pixel-level labels. These methods predominantly leverage generative adv
Externí odkaz:
https://doaj.org/article/51bed9a9409349a49ba596878be682d6
Publikováno v:
Remote Sensing, Vol 16, Iss 12, p 2148 (2024)
The spaceborne high-resolution and wide-swath synthetic aperture radar (HRWS-SAR) system combined with the ground moving target indication (GMTI) mode provides a promising prospect in the realization of wide-area target surveying and high-resolution
Externí odkaz:
https://doaj.org/article/909cfd80d1af45aaa822ac3af55dce99
Publikováno v:
PLoS ONE, Vol 19, Iss 1 (2024)
Externí odkaz:
https://doaj.org/article/c9af87c36f874f3abd36463e9b77d935
Autor:
Chenyan Li, Yangyang Hou, Minwei He, Liping Lv, Yulong Zhang, Sujing Sun, Yan Zhao, Xingzhao Liu, Ping Ma, Xiaohui Wang, Qianqian Zhou, Linsheng Zhan
Publikováno v:
Advanced Science, Vol 10, Iss 30, Pp n/a-n/a (2023)
Abstract Immunotherapy using dendritic cell (DC)‐based vaccination is an established approach for treating cancer and infectious diseases; however, its efficacy is limited. Therefore, targeting the restricted migratory capacity of the DCs may enhan
Externí odkaz:
https://doaj.org/article/670010a6b26a42339e073815d33a37c8
Autor:
Huili Xie, Xinke Wang, Zhenfeng Wang, Zhiyong Shi, Xiaoting Hu, Hong Lin, Xiangqun Xie, Xingzhao Liu
Publikováno v:
Heliyon, Vol 9, Iss 9, Pp e20130- (2023)
Rapid urbanization has gradually increased the contradiction between the demand and supply of urban resources. The quantitative optimization and adjustment of the infrastructure of the 15-min living circle is conducive to the scientific formulation o
Externí odkaz:
https://doaj.org/article/0ba5e0ccc04948e4a604a125391c6a71
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 5893-5904 (2023)
The rapid development of deep learning cannot be achieved without the support of abundant labeled data. However, obtaining such a large amount of annotated data needs the support of professionals in the field of synthetic aperture radar (SAR) image u
Externí odkaz:
https://doaj.org/article/1efde182fa81417f85324f2c5ab8ea0b
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 3805-3818 (2023)
The super-resolution algorithms based on deep learning can effectively increase optical remote sensing image (ORSI) details for further analysis tasks. Deep unfolding methods have been studied in recent years to bridge the gap between optimization-ba
Externí odkaz:
https://doaj.org/article/a5e234d82df744f7bed4b6ae273d78e7
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 3131-3147 (2023)
Image super-resolution (SR) is widely used in remote sensing because it can effectively increase image details. Neural networks have shown remarkable performance in recent years, benefitting from their end-to-end training. However, remote sensing ima
Externí odkaz:
https://doaj.org/article/4a82db14119345d89f1077b2bf818d76
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 291-305 (2023)
The development of deep learning has significantly boosted the development of ship detection in synthetic aperture radar (SAR) images. Most previous works rely on the convolutional neural networks (CNNs), which extract characteristics through local r
Externí odkaz:
https://doaj.org/article/7cffa4959f5a466dab77678c721557e8