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Abstract: We present a neural network-based face detection system. A retinally connected neural network examines small windows of an image, and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We use a bootstrap algorithm for training, which adds false detections into the training set as training progresses. This eliminates the difficult task of manually selecting non-face training examples, which must be chosen to... (Update)
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BibTeX entry: (Update)
Henry A. Rowley, Shumeet Baluja, and Takeo Kanade. Human face detection in visual scenes. CMU-CS-95-158R, Carnegie Mellon University, November 1995. Also available at http://www.cs.cmu.edu/har/faces.html. http://citeseer.ist.psu.edu/article/rowley95human.html More
@inproceedings{ rowley96human,
author = "Henry A. Rowley and Shumeet Baluja and Takeo Kanade",
title = "Human Face Detection in Visual Scenes",
booktitle = "Advances in Neural Information Processing Systems",
volume = "8",
publisher = "The {MIT} Press",
editor = "David S. Touretzky and Michael C. Mozer and Michael E. Hasselmo",
pages = "875--881",
year = "1996",
url = "citeseer.ist.psu.edu/article/rowley95human.html" }
Citations (may not include all citations):216 Phoneme recognition using time-delay neural networks (context) - Waibel, Hanazawa et al. - 1989
120 Human face detection in visual scenes - Rowley, Baluja et al. - 1995
27 Example-based learning for viewbased human face detection (context) - Sung, Poggio - 1994
6 Backpropogation applied to handwritten zip code recognition (context) - Le Cun, Boser et al. - 1989
3 Encouraging distributed input reliance in spatially constrai.. (context) - Baluja, Pomerleau - 1995
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