Restinet: an efficient deep learning approach to improve human detection accuracy

HIGHLIGHTS

• who: Shahriar Shakir Sumit from the of Computer and Information Sciences, Universiti Teknologi PETRONAS (UTP), Seri Iskandar, Perak, Malaysia Torrens University have published the article: ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy, in the Journal: (JOURNAL)

SUMMARY

ReSTiNet is a novel small convolutional neural_network that overcomes the problems of network size, detection speed, and accuracy. The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. To improve the detection speed and accuracy of ReSTiNet, the residual . . .

 



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