Zobrazeno 1 - 10
of 1 153
pro vyhledávání: '"Liangpei Zhang"'
Autor:
Di Wang, Jing Zhang, Minqiang Xu, Lin Liu, Dongsheng Wang, Erzhong Gao, Chengxi Han, Haonan Guo, Bo Du, Dacheng Tao, Liangpei Zhang
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11632-11654 (2024)
Foundation models have reshaped the landscape of remote sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning methods to initialize model weights ef
Externí odkaz:
https://doaj.org/article/f1ebc4a04ca145599622a4482d62ea54
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2489-2500 (2024)
This article addresses the problem of building segmentation for rural areas with high-resolution remote sensing images. Due to the irregular spatial distribution of rural buildings, it is often challenging to perform pixel-wise dense prediction to en
Externí odkaz:
https://doaj.org/article/4f8cb010b0694790b2700a781830091f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 719-731 (2024)
Optical and synthetic aperture radar (SAR) images provide complementary information to each other. However, the heterogeneity of same-ground objects brings a large difficulty to change detection (CD). Correspondingly, transformation-based methods are
Externí odkaz:
https://doaj.org/article/f3d698232d67422e9e539299a3c3d675
Autor:
Sunan Shi, Yanfei Zhong, Yinhe Liu, Jue Wang, Yuting Wan, Ji Zhao, Pengyuan Lv, Liangpei Zhang, Deren Li
Publikováno v:
International Journal of Digital Earth, Vol 16, Iss 1, Pp 3321-3347 (2023)
High resolution satellite images are becoming increasingly available for urban multi-temporal semantic understanding. However, few datasets can be used for land-use/land-cover (LULC) classification, binary change detection (BCD) and semantic change d
Externí odkaz:
https://doaj.org/article/102b959297a34a05b3dbfa79778b7278
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 128, Iss , Pp 103741- (2024)
Satellite video is an emerging surface observation data that has drawn increasing interest due to its potential in spatiotemporal dynamic analysis. Single object tracking of satellite videos allows the continuous acquisition of the positions and rang
Externí odkaz:
https://doaj.org/article/4503dc66397f47da9e6b37a0235d7358
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 128, Iss , Pp 103762- (2024)
The global population is on the rise, leading to an increased demand for food resources. Accurate mapping and monitoring of paddy rice fields have become crucial for effective food management and yield estimation. Several large-scale paddy rice mappi
Externí odkaz:
https://doaj.org/article/2d9bd5c24b224d16ba0cb71dc3feb8a4
Publikováno v:
Journal of Remote Sensing, Vol 4 (2024)
Paddy rice mapping is crucial for cultivation management, yield estimation, and food security. Guangdong, straddling tropics and subtropics, is a major rice-producing region in China. Mapping paddy rice in Guangdong is essential. However, there are 2
Externí odkaz:
https://doaj.org/article/4efe29a44dd94ebebfa1816a55b45fd5
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 124, Iss , Pp 103506- (2023)
Wildfires frequently occur around the world, which seriously threaten the ecology, environment, economic development, even human safety. In this work, we propose a novel framework for near-real-time and early-stage wildfire detection using Himawari-8
Externí odkaz:
https://doaj.org/article/5f22548feb00474bab1b59675ea00a88
Publikováno v:
GIScience & Remote Sensing, Vol 59, Iss 1, Pp 2036-2067 (2022)
High resolution of global land cover dynamic is indicative for understanding the influence of anthropogenic activity on environmental change. However, most of the land cover products are based on Landsat image that only has 30 m resolution, which is
Externí odkaz:
https://doaj.org/article/f79055bfffc045e9916ae5eb6117e141
Publikováno v:
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
Deep convolutional neural networks (DCNNs) have been successfully used in semantic segmentation of high-resolution remote sensing images (HRSIs). However, this task still suffers from intra-class inconsistency and boundary blur due to high intra-clas
Externí odkaz:
https://doaj.org/article/0faaf8915b014e4da793f8a45be5b26e