Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Shuhui Jiao"'
Publikováno v:
Remote Sensing, Vol 15, Iss 1, p 175 (2022)
Accurate and reliable horticultural crop classification results are an important part of agricultural management. At present, research on orchard classification based on optical images in complex mountain areas is vulnerable to the influence of cloud
Externí odkaz:
https://doaj.org/article/e3a9c3ca2bbf47f28aa99fe7973faee7
Autor:
Shuhui Jiao, Dingxiang Hu, Zhanfeng Shen, Haoyu Wang, Wen Dong, Yifei Guo, Shuo Li, Yating Lei, Wenqi Kou, Jian Wang, Huimei He, Yanming Fang
Publikováno v:
Remote Sensing, Vol 14, Iss 9, p 2015 (2022)
Accurate and reliable farmland crop mapping is an important foundation for relevant departments to carry out agricultural management, crop planting structure adjustment and ecological assessment. The current crop identification work mainly focuses on
Externí odkaz:
https://doaj.org/article/5e337754bb234579b7031280f2fabecf
Publikováno v:
Remote Sensing, Vol 13, Iss 14, p 2782 (2021)
Image segmentation plays a significant role in remote sensing image processing. Among numerous segmentation algorithms, the region-merging segmentation algorithm is widely used due to its well-organized structure and outstanding results. Many merging
Externí odkaz:
https://doaj.org/article/36177fac6d934416bfb396279276379e
Publikováno v:
Remote Sensing, Vol 13, Iss 1, p 90 (2020)
High-quality road network information plays a vital role in regional economic development, disaster emergency management and land planning. To date, studies have primarily focused on sampling flat urban roads, while fewer have paid attention to road
Externí odkaz:
https://doaj.org/article/45812c25669b43d79e36668b9ab824f4
Autor:
Haoyu Wang, Jian Wang, Zhanfeng Shen, Zihan Zhang, Junli Li, Lifang Zhao, Shuhui Jiao, Shuo Li, Yating Lei, Wenqi Kou, Jinghan Li, Jingdong Chen
Publikováno v:
International Journal of Remote Sensing. 43:6195-6220
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d69ddc574e70ac5e10e0314c5c4f670
https://doi.org/10.1080/01431161.2022.2093622
https://doi.org/10.1080/01431161.2022.2093622