Image contours detection with deep features and SVM

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Abstract

This contribution introduces the image contours detection based on the features extracted by a deep convolutional neural network. Popular pre-trained network VGG19 was used to extract 5504 different features for each input image pixel and then classified by a neural network with SVM classifier.

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APA

Molek, V. (2018). Image contours detection with deep features and SVM. In Advances in Intelligent Systems and Computing (Vol. 642, pp. 546–553). Springer Verlag. https://doi.org/10.1007/978-3-319-66824-6_48

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