Efficient Convolution Neural Networks for Object Tracking Using Separable Convolution and Filter Pruning

Object tracking based on deep learning is a hot topic in computer vision with many applications. Due to high computation and memory costs, it is difficult to deploy convolutional neural networks (CNNs) for object tracking on embedded systems with limited hardware resources. This paper uses the Siame...

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Veröffentlicht in:	IEEE access 2019, Vol.7, p.106466-106474
Hauptverfasser:	Mao, Yuanhong, He, Zhanzhuang, Ma, Zhong, Tang, Xuehan, Wang, Zhuping
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Computation Computer vision Convolution Deep learning Embedded systems Feature extraction filter pruning Information filtering Neural networks Object tracking Parameters Pruning separable convolution Tracking
Online-Zugang:	Volltext
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