首页|Data from Shenyang Agricultural University Broaden Understand- ing of Engineering (Remote Sensing Image Classification Based on Multi-Spectral Cross-Sensor Super-Resolution Combined With Tex- ture Features: A Case Study in the Liaohe Planting Area)
Data from Shenyang Agricultural University Broaden Understand- ing of Engineering (Remote Sensing Image Classification Based on Multi-Spectral Cross-Sensor Super-Resolution Combined With Tex- ture Features: A Case Study in the Liaohe Planting Area)
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2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on engineering. According to news originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “High-resolution (HR) optical remote sensing images are typically small in swath and, due to cloud cover, their revisit period, mosaic error, and other problems, it is often infeasible to obtain a large range of remote sensing images for a study area. Meanwhile, low-resolution (LR) satellite images suffer from insufficient spatial and texture information for ground objects.” Funders for this research include Liaoning Provincial Department of Education Project.
Shenyang Agricultural UniversityShenyangPeople’s Republic of ChinaAsiaEngineeringRemote Sensing
NETL
NSTL
IEEE
