A5031131275- Remote Sensing in Agriculture
- Spectroscopy and Chemometric Analyses
- Leaf Properties and Growth Measurement
- Remote Sensing and Land Use
- Water Quality Monitoring and Analysis
- Smart Agriculture and AI
- Remote Sensing and LiDAR Applications
- Land Use and Ecosystem Services
- High voltage insulation and dielectric phenomena
- Analytical Chemistry and Sensors
- Powdery Mildew Fungal Diseases
- Geology and Paleoclimatology Research
- Advanced Battery Technologies Research
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Protist diversity and phylogeny
- Plant Ecology and Soil Science
- Conducting polymers and applications
- Cell Image Analysis Techniques
- Archaeology and ancient environmental studies
- 3D Surveying and Cultural Heritage
- Reliability and Maintenance Optimization
- Ocean Waves and Remote Sensing
- Computational Geometry and Mesh Generation
- Modular Robots and Swarm Intelligence
- Genomics and Phylogenetic Studies
China Jiliang University
2025
China Agricultural University
2021-2024
Yantai Academy of Agricultural Sciences
2024
South China Normal University
2024
Ministry of Agriculture and Rural Affairs
2021-2023
Shanghai Jiao Tong University
1984-2019
University of Technology Malaysia
2015
Universiti Teknologi MARA
2015
University of Southern Queensland
2015
Estimation of leaf chlorophyll content (LCC) by proximal sensing is an important tool for photosynthesis evaluation in high-throughput phenotyping. The temporal variability crop biochemical properties and canopy structure across different growth stages has great impacts on wheat LCC estimation, known as stage effects. It will result the heterogeneity at stages, which would mask subtle spectral response biochemistry variations. This study aims to explore responses effects establish models...
Accurately predicting the State of Health (SOH) new energy vehicle batteries is critical for ensuring their reliable operation and extending battery's service life. To address issue low SOH prediction accuracy across different lengths, this paper proposes a method based on long-short-term battery degradation feature extraction FEA-TimeMixer model. First, novel automatic algorithm offline charging data introduced to label data. Then, autoencoder utilized fuse features long-term short-term...
Abstract. The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce accurate digital model (DTM). However, most these spatial filtering methods just utilizing the geometrical discriminate nonterrain points. method also can be improved by using spectral information available with some scanners. Therefore, objective this study investigate effectiveness three-channel (red, green and blue) colour image captured built-in camera...
Wide-angle synthetic aperture radar (SAR) altimeters, which are able to obtain higher azimuth resolution and better height measurement result, demonstrate a promising prospect of application. Accumulating scattering echoes received from different angles can greatly suppress noise promote estimation accuracy. However, traditional methods accumulation cannot work well in wide-angle SAR altimeters due variety characteristics. To address this problem, study first researches on basic principles,...
<title>Abstract</title> Citrus Huanglongbing (HLB) poses a significant threat to the profitability of citrus industry worldwide. In traditional agricultural practices, manually identifying trees infected with HLB based on certain leaf characteristics is time-consuming, subjective, and inefficient. The initial automatic identification relies image processing machine learning algorithms, exhibiting low accuracy slow speed. order enhance both detection speed, researchers have introduced deep...