Yi Huangfu | Image Processing | Best Researcher Award

Yi Huangfu | Image Processing | Best Researcher Award

Mr. Yi Huangfu,Yunnan Agricultural University, China.

Yi Huangfu, a postgraduate student at Yunnan Agricultural University 🎓, specializes in Smart Agriculture 🌾, focusing on Point Cloud and Image Processing, and End-to-End Object Detection and Perception 📸🤖. With a strong foundation in Computer Science from Inner Mongolia University of Science and Technology 💻, he has published impactful research on panoramic image stitching and disease detection in crops 🌽🍊. Yi has also developed an APP for Huanglongbing disease detection 📱 and holds an invention patent. Skilled in programming languages, machine learning, and Linux systems, he is passionate about advancing agricultural technology through innovation.

Publication Profile

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Education and Experience

  • 🎓 2022-2025: Master in Mechanical Design and Manufacturing, Yunnan Agricultural University
  • 🎓 2017-2021: Undergraduate in Computer Science and Technology, Inner Mongolia University of Science and Technology
  • 💻 Research: Published two papers as the first author on agricultural image processing and disease detection.
  • 🛠️ Patent: Developed a Huanglongbing detection app, earning a patent and software copyright.

Suitability for the Award

Mr. Yi Huangfu stands as an exemplary candidate for the Best Researcher Award, combining academic excellence with impactful contributions to Smart Agriculture. As a first author of groundbreaking research on crop disease detection and panoramic image processing, Yi has advanced precision farming practices. His patented innovations, including an app for Huanglongbing detection, highlight his practical expertise. Proficient in deep learning and programming, with accolades in national competitions, Yi embodies innovation and dedication in agricultural research.

Professional Development

Yi Huangfu demonstrates proficiency in deep learning, machine learning, and image processing technologies 🤖. His expertise spans Linux system programming, Java, C/C++, PHP, Python, OpenCV, and web scraping 💻. His research bridges technology and agriculture, addressing challenges in crop disease detection 🌾 using innovative solutions like the HHS-RT-DETR model and VCHS-YOLO 🌶️. Yi’s academic and technical pursuits are complemented by his strong ability to interpret English literature 📚, enabling him to stay abreast of global advancements. His contributions aim to enhance agricultural precision and productivity through cutting-edge applications 📈.

Research Focus

Yi’s research focuses on advancing Smart Agriculture 🌾 by integrating modern technologies like Point Cloud and Image Processing 📸 and Deep Learning models 🤖. His notable projects include disease detection systems for crops such as citrus and chili 🌶️🍊 and methods for image stitching in corn ear analysis 🌽. Yi’s work emphasizes creating scalable, end-to-end detection and perception systems for improving crop management efficiency 🚜. His dedication to applying AI and machine learning in agriculture bridges the gap between technology and sustainable farming 🌍.

Awards and Honors

  • 🏆 2018: NAGC Software Engineer Certificate
  • 🏅 2019: Excellent Award in the National NetGuard Security Cup
  • 🥉 2020: National Third Prize in the China College Student Programming Competition

Publication Highlights

  • 2024: HHS-RT-DETR: A Method for the Detection of Citrus Greening Disease 🍊 | Published in Agronomy 📖 
  • 2024: Research on a Panoramic Image Stitching Method for Images of Corn Ears, Based on Video Streaming 🌽 | Published in Agronomy 📖 

Assist Prof Dr. Rui Zhao | Image Processing | Best Researcher Award

Assist Prof Dr. Rui Zhao | Image Processing | Best Researcher Award

Assist Prof Dr. Rui Zhao, Ningbo University, China

Dr. Rui Zhao is a seasoned researcher with extensive expertise in remote sensing, photogrammetry, and data analysis. Holding a Ph.D. in Photogrammetry and Remote Sensing from Wuhan University, Rui’s academic journey has been marked by significant contributions to the field, including the development of innovative remote sensing applications for environmental monitoring. With over six years of industry experience, Rui has led interdisciplinary research projects at esteemed institutions such as Peking University and Meituan Travel Division, driving operational excellence and achieving key performance targets. Rui’s exceptional leadership skills, coupled with a passion for innovation, have earned them prestigious accolades, including the Silver Award of Hubei Patent Award and the Best Paper Award at the International Conference of Intelligent System and Image Processing. Through their dedication to advancing research in anomaly detection and remote sensing technologies, Rui continues to make impactful contributions to the scientific community.

Professional Profile:

Scopus

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👨‍🎓 Education

  • Ph.D. in Photogrammetry and Remote Sensing, Wuhan University, 2012-2017
  • Bachelor’s in Remote Sensing Science and Technology, Wuhan University, 2008-2012

🔬 Research Experience

  • Ningbo University Lecturer, 2022-Present
  • Peking University Boya PostDoc, 2020-2022
  • Meituan Travel Division Senior Researcher, 2018-2020
  • Huawei 2012 Lab Researcher, 2017-2018

🏆 Awards & Achievements

  • Silver Award of Hubei Patent Award, 2021
  • Best Paper Award in the 4th International Conference of Intelligent System and Image Processing (ICISIP), 2016

🚀 Projects

  • Project Leader for Anomaly Detection in High Spatial-Spectral Resolution Remote Sensing Imagery
  • Project Leader for Anomaly Detection in Hyperspectral Remote Sensing Imagery for Vegetation Monitoring
  • Project Member on Multi-Modal Remote Sensing Data Regularization and on-Orbit Intelligent Fusion Platform

Scopus Metrics:

  • 📝 Publications: 15 documents indexed in Scopus.
  • 📊 Citations: A total of 356 citations for his publications, reflecting the widespread impact and recognition of Dr. Rui Zhao’s research within the academic community.

Publication Top Notes:

  • A Novel Fully Convolutional Auto-Encoder Based on Dual Clustering and Latent Feature Adversarial Consistency for Hyperspectral Anomaly Detection
    Published in Remote Sensing, 2024.
    Authors: Rui Zhao, Zhiwei Yang, Xiangchao Meng, Feng Shao
  • Multistage Progressive Interactive Fusion Network for Sentinel-2: High Resolution for All Bands
    Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023.
    Authors: LIU XIN, Xiangchao Meng, Liu Qiang, 陈旭, Rui Zhao, Feng Shao
  • An Encoder–Decoder with a Residual Network for Fusing Hyperspectral and Panchromatic Remote Sensing Images
    Published in Remote Sensing, 2022-04.
    Authors: Rui Zhao, Shihong Du
  • Spectral-Spatial Residual Network for Fusing Hyperspectral and Panchromatic Remote Sensing Images
    Published in Remote Sensing, 2022-02.
    Authors: Rui Zhao, Shihong Du
  • GSEAD: Graphical Scoring Estimation for Hyperspectral Anomaly Detection
    Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017.
    Authors: Rui Zhao, Liangpei Zhang