Open AccessJournal Article
Multi-input Convolutional Neural Network Based on Gradient
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TL;DR: In the experiments of handwritten numbers recognition and pedestrian detection, the multi-input convolutional neural network has higher recognition rate compared with the traditional network structure, especially when the number of training time is fewer.
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Abstract: Deep learning has been a hot spot in the area of machine learning, of which the convolutional neural network is an important component. Based on the deep convolutional neural network and the edge features of characters extracted by auto-encoder, a convolutional neural network of multi-input layers was proposed, which input layers consisted of multi-input with gradient of various directions. In the experiments of handwritten numbers recognition and pedestrian detection, the multi-input network has higher recognition rate compared with the traditional network structure, especially when the number of training time is fewer. This result also provides a proof that multi-input convolutional neural network performed better with appropriate preprocessing.
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Motion Attitude Recognition and Behavior Prediction Algorithm Based on Wireless Sensor Network
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Research on the Cascade Pedestrian Detection Model Based on LDCF and CNN
Zhonggui Ma,Pan-pan Gao +1 more
- 01 Jan 2018
TL;DR: The cascade pedestrian detection model based on Local Decorrelation Channel Features (LDCF) and CNN is proposed and the experimental results show that the log-average miss rate of LDCF+CNN algorithm is lower than that of L DCF algorithm alone, and the miss rate is below 13.21%.
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Optimization of CNN and Its Application in Handwritten Numeral Recognition
TL;DR: This paper proposed the process and method applied in handwritten numeral parameter optimization based on CNN image recognition, which has a good reference value for the further application of CNN network in the field of image recognition.
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Deep graph convolutional network-based high-performance detection method for spectral domain gesture image stream
Hong Chen,Qingjia Geng,Aiyong Liu,Hongdong Zhao +3 more
- 19 Sep 2022
TL;DR: In this article , the spectral clustering method of graph wavelet neural network and support vector machine (SVM) was used as a classifier to improve the accuracy of the generated graph data.