id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_ml2dtmgkd5fgjimjvj4xtxtzqa	Anselmo Ferreira	Convolutional Neural Network approaches to granite tiles classification	2017	11	.pdf	application/pdf	9644	1292	62	In this paper, we go toward the automation of rock-quality assessment in different image resolutions by proposing the first data-driven technique applied to granite tiles classification. eep Convolutional Neural Networks (CNNs) with different archiectures, trained to classify the intrinsic patterns of granite tiles images to train the network, our approach uses lightweight neural networks on small patches of granite images, taking into account the majority voting of patches classification for the images Experiments comparing our approach against some hand-crafted descriptors and pre-trained networks show the effectiveness of the proposed technique. Pipeline of the proposed approach based on Convolutional Neural Networks for granite classification. Validation error results after 18 training epochs of the proposed (a) MNIST1 (b) MNIST2 and (c) MNIST3 CNNs for granite images classification. Convolutional Neural Network approaches to granite tiles classification Convolutional Neural Network approaches to granite tiles classification Convolutional Neural Network approaches to granite tiles classification	./cache/work_ml2dtmgkd5fgjimjvj4xtxtzqa.pdf	./txt/work_ml2dtmgkd5fgjimjvj4xtxtzqa.txt