Optimized object recognition based on neural networks via non-uniform sampling of appearance-based models

被引：0
|
作者：
Altamirano, LC [1 ]
Alvarado, M [1 ]
机构：
[1] Inst Mexicano Petr, PIMAyC, Mexico City 07730, DF, Mexico
来源：
ADVANCES IN ARTIFICIAL INTELLIGENCE - IBERAMIA 2004 | 2004年 / 3315卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：610 / 616
页数：7
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