Abstract
The non-uniform sampling of appearance-based models supported by neural networks is proposed. By using the strictly required images -obtained by applying non-uniform sampling- for modeling an object, a significant time reduction for the training process of neural networks is achieved. In addition, high levels of recognition are obtained. © Springer-Verlag Berlin Heidelberg 2004.
Cite
CITATION STYLE
Altamirano, L. C., & Alvarado, M. (2004). Optimized object recognition based on neural networks via non-uniform sampling of appearance-based models. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3315, pp. 610–616). Springer Verlag. https://doi.org/10.1007/978-3-540-30498-2_61
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