Artificial Intelligence for Biology and Agriculture [[electronic resource] /] / edited by S. Panigrahi, K.C. Ting

• Pubblicazione: Dordrecht : , : Springer Netherlands : , : Imprint : Springer, , 1998
• Edizione: 1st ed. 1998.
• Descrizione fisica: 1 online resource (IV, 262 p.)
• Disciplina: 630
• Soggetto topico: Agriculture; Optical data processing; Artificial intelligence; Plant physiology; Special purpose computers; Statistical physics; Dynamical systems; Computer Imaging, Vision, Pattern Recognition and Graphics; Artificial Intelligence; Plant Physiology; Special Purpose and Application-Based Systems; Complex Systems
• Persona (resp. second.): PanigrahiS; TingK.C
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references at the end of each chapters.
• Nota di contenuto: End-Effectors for Tomato Harvesting Robot -- A Computer Vision Method for Determining Length of Cheese Shreds -- Automated Modelling of Physiological Processes During Postharvest Distribution of Agricultural Products -- A Neuro-Fuzzy Approach to Identify Lettuce Growth and Greenhouse Climate -- Artificial Keys for Botanical Identification using a Multilayer Perceptron Neural Network (MLP) -- Video Grading of Oranges in Real-Time -- Cell Migration Analysis after In Vitro Wounding Injury with a Multi-Agent Approach -- Col or Computer Vision and Artificial Neural Networks for the Detection of Defects in Poultry Eggs -- Automatic Plankton Image Recognition -- Identification and Measurement of Convolutions in Cotton Fiber Using Image Analysis -- Fuzzy Logic for Biological and Agricultural Systems -- Robotics for Plant Production -- Three-Dimensional Image Reconstruction Procedure for Food Microstructure Evaluation.
• Titolo autorizzato: Artificial Intelligence for Biology and Agriculture
• ISBN: 94-011-5048-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910480802903321
• Lo trovi qui: Univ. Federico II