Proceedings of 1st International Conference on Image Processing
DOI: 10.1109/icip.1994.413708
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Human face recognition using neural networks

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Cited by 7 publications
(2 citation statements)
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“…Integral image at (x, y) coordinates gives the pixel sum of the coordinates above and on to the left of the (x,y). Ada boost training algorithm boost the performance of cascading amplifiers by training them appropriately so as to form a strong classifier [28]. The strong classifiers are arranged in a cascade in order of complexity, where each successive classifier is trained only on those selected samples which pass through the preceding classifiers.…”
Section: Face Detection Algorithmmentioning
confidence: 99%
“…Integral image at (x, y) coordinates gives the pixel sum of the coordinates above and on to the left of the (x,y). Ada boost training algorithm boost the performance of cascading amplifiers by training them appropriately so as to form a strong classifier [28]. The strong classifiers are arranged in a cascade in order of complexity, where each successive classifier is trained only on those selected samples which pass through the preceding classifiers.…”
Section: Face Detection Algorithmmentioning
confidence: 99%
“…In recent years it has been widely used in image processing, Reference [9] using self-organizing network for medical image segmentation. Reference [10] ~ [14] introduced uses of neural network approach to the case of image recognition to obtain satisfied effect.…”
Section: Materials Science and Information Technologymentioning
confidence: 99%