Mr. Bo Han | Agri-Tech Apps | Best Scholar Award

Mr. Bo Han | Agri-Tech Apps | Best Scholar AwardΒ 

Mr. Bo Han,Β  Xinjiang Agricultural University, China

Bo Han is a dedicated researcher in the fields of computer science and agricultural informatics, specializing in the application of deep learning for intelligent detection and grading of agricultural products. With a strong foundation in machine learning, data analysis, and big data technology, Bo has successfully led and participated in several research projects aimed at enhancing agricultural processes through artificial intelligence. His current research focuses on the development of intelligent grading systems for apples, with the goal of improving convenience and benefits for fruit farmers. 🌱🍏

Professional Profile:

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πŸŽ“ Education:

Bo Han is currently pursuing a degree in Agricultural Engineering with a major in Agricultural Information Technology at Xinjiang Agricultural University, Urumqi, China (Sep 2022 – July 2025). He previously earned a degree in Data Science and Big Data Technology from Henan Institute of Science and Technology, Xinxiang, China (Sep 2018 – July 2022). πŸŽ“

πŸ’Ό Professional Experience:

At Xinjiang Agricultural University, Bo serves as a Structuring Machine Learning Course Assistant, supporting both graduate and undergraduate students in their learning journey (Sep 2023 – Present). πŸ“š

Skills

Bo possesses strong skills in machine learning, data analysis, and big data technologies. His expertise extends to deep learning applications for agricultural product detection and grading. πŸ€–πŸ“Š

πŸ†Awards and Honors

  • Provincial First Prize Scholarship πŸ†
  • Senior Engineer, Artificial Intelligence Trainer
  • Certified Data Analyst (Intermediate) πŸ“ˆ
  • National College Student Data Analysis Competition (Second Prize)
  • China Postgraduate Electronics Competition (Second Prize)
  • National College Students Artificial Intelligence Knowledge Contest (First Prize) πŸ₯‡
  • Outstanding Graduate Students 🌟

Membership

Bo is a member of the China Computer Federation (CCF). πŸ’»

Teaching Experience

Bo is currently assisting in teaching a Structuring Machine Learning course, where he aids in the education of graduate and undergraduate students. πŸ‘©β€πŸ«πŸ‘¨β€πŸ«

Research Focus

Bo’s research focuses on the intelligent grading of apples using deep learning techniques. His projects include the development of hybrid models for apple detection, non-destructive detection of diseased apples, and enhancements in cotton boll detection using advanced YOLO models. He has also worked on various projects related to virtual wheat growth simulation and the prediction of nitrogen application amounts for wheat. 🍎🌾

Publication Top Note:

  • Rep-ViG-Apple: A CNN-GCN Hybrid Model for Apple Detection in Complex Orchard Environments
    Year : 2024
  • COTTON-YOLO: Enhancing Cotton Boll Detection and Counting in Complex Environmental Conditions Using an Advanced YOLO Model
    Year : 2024
  • Lightweight Non-Destructive Detection of Diseased Apples Based on Structural Re-Parameterization Technique
    Year : 2024

 

 

Mr. zhenguo zhang | Agri-Tech Awards | Best Researcher Award

Mr. zhenguo zhang | Agri-Tech Awards | Best Researcher Award

Mr. zhenguo zhang, Xinjiang Agricultural University, China

Dr. Zhang is an Associate Professor at Xinjiang Agricultural University, specializing in agricultural mechanization. He earned his Doctoral Degree in Agricultural Mechanization Engineering from China Agricultural University (2017-2023) and holds Bachelor’s degrees from Shihezi University and Ludong University. Dr. Zhang has led significant research projects funded by the National Natural Science Foundation of China, focusing on selective harvesting methods and high-efficiency mechanisms for safflower. His academic contributions include influential papers on advanced harvesting technologies and filament detection, published in leading journals like Transactions of the Chinese Society of Agricultural Engineering and Agronomy. His role as a Master’s supervisor highlights his expertise and leadership in the field.

Suitability for the Best Researcher Award:

Mr. Zhenguo Zhang’s extensive research in agricultural mechanization, combined with his significant contributions to the field through both academic publications and patented technologies, positions him as a leading figure in agricultural engineering. His work not only advances theoretical knowledge but also translates into practical solutions that address real-world challenges in crop harvesting. This combination of innovative research, practical application, and leadership in his field makes him an excellent candidate for the Best Researcher Award.

Professional Profile🌍

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Education πŸŽ“

Dr. Zhang earned his Doctoral Degree in Agricultural Mechanization Engineering from China Agricultural University (2017-2023), highlighting his advanced specialization in the field. He completed his Bachelor’s Degrees at Shihezi University (2010-2013) and Ludong University (2006-2010), providing a strong foundation in agricultural mechanization and mechanical design.

Professional Experience πŸ‘¨β€πŸ«

Dr. Zhang has an extensive academic career at Xinjiang Agricultural University, where he has advanced from Teaching Assistant to Associate Professor. His role as a Master’s supervisor underscores his expertise and leadership in agricultural mechanization.

Research Projects πŸ”¬

He has led several significant research projects funded by the National Natural Science Foundation of China, including:

  • Selective Harvesting Method for Safflower Filaments (2023-2026): Utilizing Convolutional Neural Networks and Ant Colony Algorithms.
  • High-efficiency Harvesting Mechanism for Safflower (2020-2022): Focused on developing low-loss harvesting techniques.

Academic Achievements πŸ“

Dr. Zhang has authored numerous influential papers in esteemed journals, including:

  • “Design and experiments of the circular arc progressive type harvester for safflower filaments” (Transactions of the Chinese Society of Agricultural Engineering).
  • “Detecting safflower filaments using an improved YOLOv3 under complex environments” (Transactions of the Chinese Society of Agricultural Engineering).
  • “Improved Faster R-CNN Model Based on Split Attention for Safflower Filament Detection” (Agronomy).

Publication Top Notes:

  • Improved Faster Region-Based Convolutional Neural Networks (R-CNN) Model Based on Split Attention for the Detection of Safflower Filaments in Natural Environments
    • Year: 2023
    • Citations: 5
  • Detecting Safflower Filaments Using an Improved YOLOv3 Under Complex Environments
    • Year: 2023
    • Citations: 8
  • Design and Experiment of Side-Shift Stubble Avoidance System for No-Till Wheat Seeder Based on Deviation-Perception Fusion Technology
    • Year: 2023
    • Citations: 2
  • Design and Experiment of Double-Guide Sliding Deflection System for No-Till Wheat Seeder
    • Year: 2022
    • Citations: 3
  • Design and Test of Double-Acting Opposite Direction Cutting End Effector for Safflower Harvester
    • Year: 2022
    • Citations: 7

 

 

Mr. Wei Fan | Agri-Tech Apps Awards | Best Researcher Award

Mr. Wei Fan | Agri-Tech Apps Awards | Best Researcher Award

Mr. Wei Fan, Inner Mongolia University, China

Mr. Wei Fan is currently pursuing a Ph.D. in Electronic Information at Inner Mongolia University, building on his solid academic foundation with a B.S. in Measurement and Control Technology from Inner Mongolia University of Science and Technology. His research focuses on enhancing LIDAR-based SLAM for robotics by integrating dynamic object removal capabilities. Mr. Fan has demonstrated exceptional leadership as a Student Leader and Learning Committee Member, contributing to class management, academic supervision, and event planning. His dedication to innovation is underscored by his achievements, including winning the Gold Award at the China International “Internet+” Innovation and Entrepreneurship Competition and the Provincial First Prize in the “Zhao Yi Cup” Chinese Graduate Electronic Design Competition.

Professional Profile:

Orcid

πŸŽ“ Education:

  • Ph.D. in Electronic Information
    Inner Mongolia University, China (09.2022 – Present)
  • B.S. in Measurement and Control Technology
    Inner Mongolia University of Science and Technology, China (09.2018 – 07.2022)

    • Key Courses: Intelligent Control, Random Signals, Circuit Design, Fuzzy Control, Matrix Theory, etc.

πŸ’Ό Professional Experience:

  • Student Leader, Learning Committee Member
    Responsible for class management, communication, event planning, academic supervision, and logistics support, fostering class harmony and development.

🌱 Campus Projects:

  • Graduate Research Project on Dynamic Environment Robust Fast LIDAR Odometry and Mapping
    Focuses on integrating dynamic object removal capabilities into LIDAR-based SLAM for enhanced accuracy in robotics.
  • National Key R&D Project on Eco-management of Grassland Livestock Balance
    Uses integrated sky-ground technology for tracking and behavior recognition of livestock, predicting grass growth models, and implementing precision grazing using deep learning techniques.

πŸ† Achievements:

  • Winner of various prestigious awards including the 10th China International “Internet+” Innovation and Entrepreneurship Competition Gold Award and the 19th “Zhao Yi Cup” Chinese Graduate Electronic Design Competition Provincial First Prize.

πŸŽ–οΈ Honors:

  • Recipient of scholarships and awards such as the Inner Mongolia University Graduate Scholarship and recognition as an exemplary student.

Publication Top Note:

Prediction of Health Status of Small-Tailed Cold Sheep Based on Improved BP Neural Network