Title :
Where-What Network 5: Dealing with scales for objects in complex backgrounds
Author :
Song, Xiaoying ; Zhang, Wenqiang ; Weng, Juyang
Author_Institution :
Sch. of Comput. Sci., Fudan Univ., Shanghai, China
fDate :
July 31 2011-Aug. 5 2011
Abstract :
The biologically-inspired developmental Where-What Networks (WWN) are general purpose visuomotor networks for detecting and recognizing objects from complex backgrounds, modeling the dorsal and ventral streams of the biological visual cortex. The networks are designed for the attention and recognition problem. The architecture in previous versions were meant for a single scale of foreground. This paper focuses on Where-What Network-5 (WWN-5), the extension for multiple scales. WWN-5 can learn three concepts of an object: type, location and scale.
Keywords :
learning (artificial intelligence); neural nets; object detection; object recognition; visual perception; attention problem; biological visual cortex; biologically-inspired developmental where-what network; complex background; dorsal stream modeling; general purpose visuomotor network; learning; neural network; object detection; object location; object recognition; object scale; object type; recognition problem; ventral stream modeling; Computational modeling; Computer architecture; Educational institutions; Neurons; Retina; Shape; attention; neural networks; object recognition; recognition; scale invariance;
Conference_Titel :
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-9635-8
DOI :
10.1109/IJCNN.2011.6033587
