@inproceedings{ef5ee70530f84d579984b08629b9123f,
title = "Deep neural networks for free-hand sketch recognition",
abstract = "The paper presents a deep Convolutional Neural Network (CNN) framework for free-hand sketch recognition. One of the main challenges in free-hand sketch recognition is to increase the recognition accuracy on sketches drawn by different people. To overcome this problem, we use deep Convolutional Neural Networks (CNNs) that have dominated top results in the field of image recognition. And we use the contours of natural images for training, because sketches drawn by different people may be very different and databases of the sketch images for training are very limited. We propose a CNN training on contours that performs well on sketch recognition over different databases of the sketch images. And we make some adjustments to the contours for training and reach higher recognition accuracy. Experimental results show the effectiveness of the proposed approach.",
keywords = "Contour, Deep convolutional neural networks, Sketch recognition",
author = "Yuqi Zhang and Yuting Zhang and Xueming Qian",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 17th Pacific-Rim Conference on Multimedia, PCM 2016 ; Conference date: 15-09-2016 Through 16-09-2016",
year = "2016",
doi = "10.1007/978-3-319-48896-7\_68",
language = "英语",
isbn = "9783319488950",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "689--696",
editor = "Enqing Chen and Yun Tie and Yihong Gong",
booktitle = "Advances in Multimedia Information Processing – 17th Pacific-Rim Conference on Multimedia, PCM 2016, Proceedings",
}