Introduction
Shijun Pan is a D3 Student from Okayama University, Japan. The Research Interest is Applications of deep learning technologies and image processing in river management and river engineering. Seeking research collaboration with Environmental, AI, and remote-sensing researchers. Job internship is in search.
Disciplines
Civil Engineering, Environmental Science, Artificial Intelligence
Skills and expertise
1. Object Detection (YOLOv5/v7/v8)
2. Semantic Segmentation (DeepLabV3+)
3. LiDAR Visualization, (ALB, GLS)
4. Structure From Motion, Photogrammetry
5. AIGC (Stable Diffusion, Large Multi-Modal Model)
ResearchGate
https://www.researchgate.net/profile/Shijun-Pan-2/research
Publication
1. Application of the Prompt Engineering-assisted Generative AI for the Drone-based Riparian Waste Detection
DOI: 10.11532/jsceiiai.4.2_50
2. Detection and Segmentation of Riparian Asphalt Paved Cracks Using Drone and Computer Vision Algorithms
DOI: 10.11532/jsceiiai.4.2_35
3. Drone-LiDAR-assisted Image Fusion methodology for Deep Learning-based Land Cover Classification
DOI: 10.11532/jsceiii.3.3_15
4.Airborne LiDAR-assisted deep learning methodology for riparian land cover classification using aerial photographs and its application for flood modelling
DOI: 10.2166/hydro.2022.134
WX
pannaplucky
Videos：0
Abstracts：4
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| Date | Time | Room | Session | Role | Topic |
|---|---|---|---|---|---|
| 2024-05-27 | 16:15-16:30 | Conference Room 8 第八会议厅 |
S6.5 Technologies for water management and monitoring (VII) |
Speaker | Utilizing Smartphone-derived Photogrammetry 3D Model for AI-based Riparian Crack Segmentation and Measurement |
| 2024-05-28 | 14:15-14:30 | Conference Room 9 第九会议厅 |
S2.3 Emerging solutions in modelling methods (II) |
Speaker | An Evaluation of Different Annotation Approaches for YOLOv8 Instance Segmentation in UAV Imagery: A Case Study on the UAV-BD Dataset |
| 2024-05-28 | 15:45-16:00 | Conference Room 1第一会议厅 |
S5.4 Complex water systems, remote sensing and control (II) |
Speaker | Evaluation of Segment Anything Model for Riparian Land Cover Classification from Aerial Imagery |
| 2024-05-28 | 16:00-16:15 | Conference Room 1第一会议厅 |
S5.4 Complex water systems, remote sensing and control (II) |
Speaker | The Interchangeability of the Cross-Platform Data in the Deep Learning-based Land Cover Classification Methodology |