- 期刊
- OpenAccess
Connectivity Strategies for Second-order Neural Networks Applied to Rotation Invariant Compact Disk Recognition
應用在辨識任意角度旋轉光碟片的二階神經網路連結策略
並列摘要
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.
延伸閱讀
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