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Ensemble feature learning for material recognition with convolutional neural networks
2018
EURASIP Journal on Image and Video Processing
Material recognition is the process of recognizing the constituent material of the object, and it is a crucial step in many fields. Therefore, it is valuable to create a system that could achieve material recognition automatically. This paper proposes a novel approach named ensemble learning for material recognition with convolutional neural networks (CNNs). In the proposed method, firstly, a CNN model is trained to extract the image features. Secondly, knowledge-based classifiers are learned
doi:10.1186/s13640-018-0300-z
fatcat:si3wvpmjonakneqi75cd5zj77a