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- W2516488393 abstract "This research presents novel artificial vision techniques applied to the detection of features for strawberries used in the food industry. For this purpose, a computer vision system based in artificial neural networks is used, organized as a deep architecture and trained with noise compensated learning. This combination originates a strong network - object relations which makes possible the recognition of complex strawberry features under changing conditions of lightning, size and orientation. The programming uses OpenCV libraries and fruits databases captured with a webcam. The images used to train the Artificial Neural Network are defined with canny edge detection and a moving region of interest (ROI). After training, the network recognizes important features such as shape, color and anomalies. The system has been tested in real time with real images." @default.
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- W2516488393 date "2016-06-01" @default.
- W2516488393 modified "2023-09-30" @default.
- W2516488393 title "Artificial Vision Techniques to Optimize Strawberry's Industrial Classification" @default.
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- W2516488393 doi "https://doi.org/10.1109/tla.2016.7555221" @default.
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