@inproceedings{9961ba1e6f8f48a5b796e286c89f51f3,
title = "The application of a convolution neural network on face and license plate detection",
abstract = "In this paper, two detectors, one for face and the other for license plates, are proposed, both based on a modified convolutional neural network(CNN) verifier. In our proposed verifier, a single feature map and a fully connected MLP were trained by examples to classify the possible candidates. Pyramid-based localization techniques were applied to fuse the candidates and to identify the regions of faces or license plates. In addition, geometrical rules filtered out false alarms in license plate detection. Some experimental results are given to show the effectiveness of the approach.",
keywords = "Convolution neural network, Face detection, Feature map, License plate detection",
author = "Chen, {Ying Nong} and Han, {Chin Chuan} and Wang, {Cheng Tzu} and Jeng, {Bor Shenn} and Fan, {Kuo Chin}",
year = "2006",
doi = "10.1109/ICPR.2006.1115",
language = "???core.languages.en_GB???",
isbn = "0769525210",
series = "Proceedings - International Conference on Pattern Recognition",
pages = "552--555",
booktitle = "Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006",
note = "18th International Conference on Pattern Recognition, ICPR 2006 ; Conference date: 20-08-2006 Through 24-08-2006",
}