Titlebook: Artificial Intelligence for Biology and Agriculture; S. Panigrahi,K. C. Ting Book 1998 Springer Science+Business Media Dordrecht 1998 arti

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Color Computer Vision and Artificial Neural Networks for the Detection of Defects in Poultry Eggs, accuracy of 92.8%. The neural network model for dirt stained eggs had an average accuracy of 85.0%. The average accuracy of the crack detection neural network was 87.8%. These accuracy levels were sufficient to produce graded samples that would exceed the USDA requirements.

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Automatic Plankton Image Recognition,ent features and Fourier boundary descriptors with gray-scale morphological granulometries to form a feature vector capturing both shape and texture information of plankton images. With an improved learning vector quantization network classifier, we achieve 95% classification accuracy on six plankto

uncertain

Robotics for Plant Production,lants are expected to change their shape and size during growth and development. Robotics technology includes many sub-topics including the manipulator mechanism and its control, end-effector design, sensing techniques, mobility, and workcell development. The robots which are to be used for performi

Substance

End-Effectors for Tomato Harvesting Robot, The first prototype endeffector consisted of two parallel plate fingers and a suction pad. The fingers pick a fruit off at the joint of its peduncle after the suction cup singulates it by vacuum from other fruits in the same cluster. From the results of harvesting experiment, the end-effector could

NOT

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