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Grape maturity estimation based on seed images and neural networks. Computer vision-a objective, rapid and non-contact quality evaluation tool for the food industry.

Architectures, Algorithms, and Applications. Pattern recognition of fruit shape based on the concept of chaos and neural networks. Housing Studies, 17 6pp.

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Journal Food Engineering, ; Neural network modelling to predict weekly yields of sweet peppers in a commercial greenhouse. Predictions of apple bruise volume using artificial neural network.

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Secretariado de Publicaciones de la Universidad de Murcia. The Roots of Backpropagation: Classification of fruits by a boltzmann perceptron neural network, Automatica, ; 28 5: Foreword, ; 87 1: Enero – Marzo; ; ; Part C, ; Computers and Electronics in Agriculture, ; 18 Computers of Electronics in Agriculture, ; Scientia Horticulturae, ; Immature peach detection in colour images acquired in natural illumination conditions using statistical classifiers and neural network.

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Classification of fruits using Probabilistic Neural Networks – Improvement using color features. Procedia Computer Science, ; Perth, Western Australia, January.

Prediction of mass transfer kinetics during osmotic dehydration of apples using neural networks. Comparison between neural network and multiple regression approaches: An Artificial Neuronal Network real estate price predictor.

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Methodologies, Perspectives, and Applications. Apple classification based on surface bruises using image processing and neural aprticadas. Computers and Electronics in Agriculture, ; 29 Classification of apple surface features using machine vision and neural networks. An intelligent control for greenhouse automation, oriented by the concepts of SPA and SFA – an application to a post-harvest process.

Modeling of physical properties of apple slices Golab variety using artificial neural networks. Land Concretk Review; 2 1pp. Select Page with selected: Apple sorting using artificial neural networks and spectral imaging. Lett, ; 28