Dianhan Xi

The University of Tokyo — Japan

Environmental Science · Physical Sciences

9h-index190citations22works8.62yr avg
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Research Topics

Remote Sensing and LiDAR Applications(6), Remote Sensing in Agriculture(4), Smart Agriculture and AI(4), Image Enhancement Techniques(3), Advanced Neural Network Applications(2)

Publications22 total

Synthetic Data Augmentation for Coral Health Detection: A Joint Training Approach with CycleGAN and UNIT
2025
A novel underwater Holothurians monitoring system using consumer-grade amphibious UAV with Mamba-based Super-Resolution Reconstruction and enhanced YOLOv10
Marine Environmental Research·2025· 6 cited
Succulent-YOLO: Smart UAV-Assisted Succulent Farmland Monitoring with CLIP-Based YOLOv10 and Mamba Computer Vision
Remote Sensing·2025· 15 citedOpen Access
Enhanced hermit crabs detection using super-resolution reconstruction and improved YOLOv8 on UAV-captured imagery
Marine Environmental Research·2025· 5 citedOpen Access
Deep Learning-Driven Super-Resolution and DenseCLIP-Based Semantic Segmentation for Coral Reef Mapping
2025
Smart UAV-assisted blueberry maturity monitoring with Mamba-based computer vision
Precision Agriculture·2025· 14 citedOpen Access
UAV-Assisted Succulent Farmland Monitoring with Improved YOLOv10 and MambaIR
2025· 2 cited
Underwater Sea Cucumber Detection Using Consumer-Grade Amphibious UAV and Deep-Learning Based Computer Vision
2025· 4 cited
Seafloor debris detection using underwater images and deep learning-driven image restoration: A case study from Koh Tao, Thailand
Marine Pollution Bulletin·2025· 17 citedOpen Access
Smart UAV-assisted rose growth monitoring with improved YOLOv10 and Mamba restoration techniques
Smart Agricultural Technology·2024· 18 citedOpen Access
Riverbed litter monitoring using consumer-grade aerial-aquatic speedy scanner (AASS) and deep learning based super-resolution reconstruction and detection network
Marine Pollution Bulletin·2024· 24 citedOpen Access
Consumer-Grade Aerial-Aquatic Speedy Scanner (AASS) for Efficient Underwater Monitoring with Deep Learning
2024· 9 cited
A New Coral Classification Method Using Speed Sea Scanner-Portable and Deep Learning-Based Point Cloud Semantic Segmentation
2024· 9 cited
Super-Resolution Approaches Based Shallow-Water Benthic Identification Using Multispectral Satellite Imagery
2024· 8 cited
YOLOv10 and Mamba-Based Super-Resolution for Smart Rose Growth Monitoring Using UAV Imagery
2024· 9 cited
Drone-Based Aerial Data can Detect Cabbage Heads Based on Super-Resolution and Segmentation Network
2024
Mamba-Based Super-Resolution and Segmentation Network for UAV-Captured Blueberry Farmland Imagery
2024· 11 cited
Enhanced hermit crabs detection using super-resolution reconstruction and improved YOLOv8 on UAV-captured imagery
arXiv (Cornell University)·2024· 1 citedOpen Access
A Deep Learning Approach Combining Super-Resolution and Segmentation to Identify Weed and Tobacco in UAV Imagery
2024· 16 cited
Basic Study of Deep Learning Based Efficient Hermit Crabs Detection from Drone-Captured Images
2024· 12 cited
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Frequent Co-authors

Yongying Liu(16), Xinlei Shao(15), Yijia Chen(11), Fan Zhao(9), Katsunori Mizuno(9), Bangzhang Ma(9), Jiaqi Wang(8), Jiaqi Wang(7), Jiaqi Wang(6), Yijia Chen(6), Guochen Zhang(6), Yulun Chen(6), Yinyin He(6), Katsunori Mizuno(6), Fan Zhao(6), Shigeru Tabeta(5), Fan Zhao(5), Qingyang Wu(5), Zhiyan Ren(4), Jundong Chen(4)