Built on the theories of biological neural network, artificial neural network methods have shown many significant advantages. However, the memory space in an artificial neural chip...
A new model which can recognize rotated, distorted, scaled, shifted and noised patterns is proposed. The model is constructed based on psychological experiments in a mental rotatio...
Training convolutional neural networks (CNNs) on large sets of high-resolution images is too computationally intense to be performed on commodity CPUs. Such architectures however ...
Pattern recognition problems span a broad range of applications, where each application has its own tolerance on classification error. The varying levels of risk associated with ma...
This paper presents FC networks that are instantaneously trained neural networks that allow rapid learning of non-binary data. These networks, which generalize the earlier CC netw...