关键词: 宽度学习网, 局部感受野, 神经网络, 图像分类

Abstract:

In order to identify images more quickly and accurately, this paper puts forward the Local Receptive Field based Broad Learning System（BLS-LRF） algorithm, this method is based on the Broad Learning System（BLS） model and combines with the idea of Local Receptive Field（LRF） to extract the image features from two aspects：local feature and global feature. Two kinds of image data sets are used to study the network, and the results are compared with many traditional neural networks. The results show that the test accuracy of the BLS-LRF network not only exceeds the test accuracy of the traditional network, but also greatly shortens the time required for the training process.

Key words: broad learning system, Local Receptive Field（LRF）, neural network, image classification