Agricultural produce grading by computer vision using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InProceedings{Yimyam:2012:ROBIO,

• author = "Panitnat Yimyam and Adrian F. Clark",
• booktitle = "IEEE International Conference on Robotics and Biomimetics (ROBIO 2012)",
• title = "Agricultural produce grading by computer vision using Genetic Programming",
• year = "2012",
• month = "11-14 " # dec,
• address = "Guangzhou",
• pages = "458--463",
• keywords = "genetic algorithms, genetic programming, agriculture, computer vision, crops, image classification, image colour analysis, image segmentation, image texture, inspection, learning (artificial intelligence), shape recognition, agricultural produce grading, apple variety discrimination, barley classification, colour feature, feature classification, feature segmentation, generic component, machine learning, mango surface inspection, maturity evaluation, purple sticky rice grading, shape feature, task-specific computer vision system, texture feature, wheat classification",
• isbn13 = "978-1-4673-2125-9",
• DOI = "doi:10.1109/ROBIO.2012.6491009",
• size = "6 pages",
• abstract = "An approach to generating task-specific computer vision systems from generic components using machine learning is presented. With this system, it is possible to learn both feature segmentation and classification from training data. This approach is applied to a disparate range of problems in the domain of agricultural produce grading: mango surface inspection and maturity evaluation, apple variety discrimination, wheat and barley classification and purple sticky rice grading. It is shown that shape, colour and texture features together produce more accurate classification results than fewer categories of feature, and that these evolved classifiers are competitive with neural networks and support vector machines.",
• notes = "Also known as \cite{6491009}",

}

Genetic Programming entries for Panitnat Yimyam Adrian F Clark

Citations