Connectivity Strategies for Second-order Neural Networks Applied to Rotation Invariant Compact Disk Recognition
Tai-Ning Yang, Chih-Jen Lee, Chun‐Jung Chen, Shi-Jim Yen · International conference on Artificial intelligence and applications · 2007
A second-order neural network is designed to be invariant to changes in rotation. Rotation invariance is achieved through a special arrangement of the network structure. The training set only requires one view of each target object. We describe the weight sharing strategy and present a compact disk recognition neural network illustrating its usefulness. The simulation results show that the proposed neural network can distinguish between the target compact disks independent of the transformation in rotation.