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This book collects transforming technologies in smart agriculture and their applications during the past decade. It focuses on the latest sensing and automation technologies for field and specialty crop production, and provides a lot of innovative knowledge on imaging processing, AI algorithms, robotics, and their applications in agriculture. It provides undergraduate or graduate students take-away knowledge for unmanned agriculture production, including but not limited to, corn/wheat disease detection, cotton yield prediction, and apple detection. Furthermore, this book includes review reports on plant phenotyping sensing and automation technologies and techniques for aphid detection.
Provides a comprehensive and latest technology progress in smart agriculture Presents new technologies on rock picking in agriculture Discusses new robotic technology on phenotyping
Auteur
Dr. Zhao Zhang received his B.E. and M.E. degrees in Industrial Engineering and Agricultural Mechanization from Northwest A&F University in 2009 and 2012, respectively, and the Ph.D. degree in Agricultural Engineering from The Pennsylvania State University, U.S., in 2015. Since Nov. 2021, Dr. Zhang has been in College of Information and Electrical Engineering, China Agricultural University as a Professor.
Yongxin Jiang was born in 1975, graduated from China Agricultural University at Beijing with Ph.D. degree in agricultural engineering in 2023 and now is a research professor at Research Institute of Agricultural Mechanization, Xinjiang Academy of Agricultural Sciences, Urumqi. Professor Jiang's major research fields include development and demonstration of farmland waste mulch recycling and resource utilization equipment. He has won provincial and ministerial level of scientific and technological progress 4 times, authorized the invention of 25 patents, published more than 30 papers.
Chunhui Wen was born in 1966 and has earned his bachelor's degree in agriculture and agricultural technology extension from Department of Plant Protection, Jiangxi Agricultural University in 1986. His major professional research direction includes plant protection and facility vegetable planting technology. He has won the second prize of the Harvest Plan Award of the Ministry of Agriculture twice and the third prize of the Provincial Department of Agriculture, Animal Husbandry and Fisheries. He has also earned Technical Improvement Award three times and serves as Director of the Jiangxi Plant Pathology Society.
Shuyuan Men is an associate professor of the Gongqing College of Nanchang University, and he mainly works on teaching methodology studies for both undergraduate and graduate students. He has won more than 10 awards such as "Excellent University Worker", and "Advanced Individual" from Nanchang University. So far, he has published over 10 papers.
Yuan Zhang is affiliated with Institute of Agricultural Machinery, Chinese Academy of Tropical Agricultural Sciences and he is an associate professor. He is currently the director of the research office of his unit, the director of the provincial and municipal engineering technology research centers, and the director of the municipal key laboratory. He mainly carries out agricultural engineering technology research and extension work, and has participated in 18 research projects including national key R&D Projects, and has published 17 papers and authorized 21 patents. In addition, he has issued 5 industry standards and organized 12 local/group standards. He has won the second and third prizes of Guangdong Province Machinery Industry Science and Technology Award, the third prize of Guangdong Province Agricultural Technology Promotion Award, the Guangdong Province Outstanding Scientific and Technological Achievement Award, and the second prize of Zhanjiang Science and Technology Progress Award.
Contenu
Chapter 1 A Review of Field Plant Phenotyping Platform, Sensing and Navigation Technology.- Chapter 2 Precision Handling of Green Apples in Orchard Environments Using Computer Vision.- Chapter 3 Corn Diseased Leaf Segmentation under Different Illumination Conditions.- Chapter 4 Research on Field Cotton Yield Prediction System Based on Improved YOLOv5 Cotton Detection Model and Android Development.- Chapter 5 Automatic segmentation algorithm for wheat field images based on UAV.- Chapter 6 Aphid Detection Techniques: A State-of-Art Review.- Chapter 7 A Comprehensive Analysis of Different Object Detection Frameworks and Path Optimization Algorithms for an RGB-D Camera-based Rock Detection System.
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