Computer vision-based agriculture engineering

"Computer Vision-Based Agriculture Engineering is a summary of the author's work over the past 10 years. Professor Han has presented his most recent research results in the book of all 25 chapters. This unique work provides student, engineers and technologists working in research, development, and operations in the agricultural engineering with critical, comprehensive and readily accessible information. The book applies development of artificial intelligence theory and methods including depth learning and transfer learning to the field of agricultural engineering testing"--

Machine generated contents note: ch. 1 Detecting Anatoxin in Agricultural Products by Hyperspectral Imaging: A Review -- 1.1.Introduction -- 1.2.Main Detecting Methods -- 1.2.1.Hyperspectral Imaging (HSI) -- 1.2.2.Near-Infrared Spectroscopy (NIRS) -- 1.2.3.Flow Chart Showing Typical Steps -- 1.3.Detection of Anatoxin in Agricultural Products -- 1.3.1.Corn or Maize -- 1.3.1.1.Detection of Anatoxin by Hyperspectral Images -- 1.3.1.2.Detection of Anatoxin by Other Methods -- 1.3.1.3.Detect Other Fungi -- 1.3.2.Cereals, Nuts, and Others -- 1.3.2.1.Wheat, Barley, and Rice -- 1.3.2.2.Pistachio Nuts, Hazelnuts, Brazil Nuts, and Peanuts -- 1.3.2.3.Chili Pepper -- 1.4.Limitation and Future Trends -- 1.4.1.Limitation -- 1.4.2.Future Trends -- 1.5.Conclusions -- References -- ch. 2 Anatoxin Detection by Fluorescence Index and Narrowband Spectra Based on Hyperspectral Imaging -- 2.1.Introduction -- 2.2.Experiment Materials -- 2.2.1.Sample Preparation and Image Acquisition -- 2.2.2.Illumination Compensation and Kernel Segmentation -- 2.3.Data Processing and Result Analysis -- 2.3.1.Fluorescence Index -- 2.3.2.Recognition and Regression -- 2.3.3.Narrowband Spectra -- 2.4.Discussion -- 2.5.Concl…