Target recognition based on convolutional neural network

Liqiang Wang; Xin Wang; Fubiao Xi; Jian Dong

doi:10.1117/12.2292889

15 November 2017 Target recognition based on convolutional neural network

Liqiang Wang, Xin Wang, Fubiao Xi, Jian Dong

Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 106052A (2017) https://doi.org/10.1117/12.2292889
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China

Abstract

One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

Citation Download Citation

Liqiang Wang, Xin Wang, Fubiao Xi, and Jian Dong "Target recognition based on convolutional neural network", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 106052A (15 November 2017); https://doi.org/10.1117/12.2292889

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