Title :
Object recognition by a Hopfield neural network
Author :
Nasrabadi, Nasser M. ; Li, Wei ; Choo, Chang Y.
Author_Institution :
Dept. of Electr. Eng., Worcester Polytech. Inst., MA, USA
Abstract :
A model-based recognition method is introduced which is formulated as an optimization problem. An energy function is derived which represents the constraints on the best solution in order to find the best match. A two-dimensional binary Hopfield neural network is implemented to minimize the energy function. The state of each neuron in the Hopfield network represents the possibility of a match between a node in the model graph and a node in the scene graph
Keywords :
computer vision; computerised pattern recognition; computerised picture processing; neural nets; best match; best solution; energy function; minimize; model graph; neuron; node; object recognition; optimization problem; scene graph; two-dimensional binary Hopfield neural network; Computer vision; Hopfield neural networks; Layout; Neural networks; Neurons; Object recognition; Parallel processing; Robot vision systems; Service robots; Testing;
Conference_Titel :
Computer Vision, 1990. Proceedings, Third International Conference on
Conference_Location :
Osaka
Print_ISBN :
0-8186-2057-9
DOI :
10.1109/ICCV.1990.139542
