š¼ Professional Profiles:
SCOPUS
š Educational Journey:
Bachelor of Engineering (B.E.) in Remote Sensing Science and Technology from Xi’an University of Science and Technology (2013-2017).
Master of Science in Cartography and Geographic Information Systems from Chang’an University (2017-2019).
Currently pursuing a Doctor of Science in Geological Information System at Chang’an University (2019-present).
š¬ Research Focus:
Dr. Dong’s expertise lies in leveraging cutting-edge technologies for remote sensing and image analysis, with a particular emphasis on:
Building edge detection from high-resolution remote sensing imagery.
Shadow detection in remote sensing images and its application to building extraction.
High-resolution remote sensing image segmentation using advanced convolutional neural networks.
Multilateral semantic approaches with dual relation networks for remote sensing image segmentation.
š Field of Expertise:
Remote Sensing Science and Technology
Remote Sensing Data Processing and Analysis
Machine Learning
Deep Learning/Computer Vision
š Dr. Xueyan Dong’s Top Noted Publications:
[2018] Dense Connected Edge Feature Enhancement Network for Building Edge Detection from High Resolution Remote Sensing Imagery
[2019] A Review of Research on Remote Sensing Image Shadow Detection and Application to Building Extraction
[2020] U-shape Nonsubsampled Contourlet Convolution Neural Networks for High Resolution Remote Sensing Image Segmentation
[2021] Multilateral Semantic with Dual Relation Network for Remote Sensing Images Segmentation
š¬ Dr. Xueyan Dong’s Scientific Research:
Building Edge Detection (2018):
- Focus: Dense Connected Edge Feature Enhancement Network for Building Edge Detection from High Resolution Remote Sensing Imagery.
- Objective: Develop enhanced methods for accurately detecting building edges in high-resolution remote sensing imagery.
- Impact: š Advancement in urban mapping and infrastructure analysis.
Shadow Detection and Building Extraction (2019):
- Focus: A Review of Research on Remote Sensing Image Shadow Detection and Application to Building Extraction.
- Objective: Evaluate and propose methodologies for shadow detection in remote sensing images, with application to building extraction.
- Impact: š” Enhancing precision in urban planning and object extraction.
High-Resolution Image Segmentation (2020):
- Focus: U-shape Nonsubsampled Contourlet Convolution Neural Networks for High Resolution Remote Sensing Image Segmentation.
- Objective: Develop advanced segmentation techniques for high-resolution remote sensing images.
- Impact: š°ļø Improved accuracy in land cover classification and environmental monitoring.