Panyu Liu1, Huilin Ren2, Xiaojun Shi3, Yangyang Li4, *, Zhiping Cai1, Fang Liu5, Huacheng Zeng6
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2321-2334, 2020, DOI:10.32604/cmc.2020.010522
- 16 September 2020
Abstract Deep learning technology has been widely used in computer vision, speech
recognition, natural language processing, and other related fields. The deep learning
algorithm has high precision and high reliability. However, the lack of resources in the edge
terminal equipment makes it difficult to run deep learning algorithms that require more
memory and computing power. In this paper, we propose MoTransFrame, a general model
processing framework for deep learning models. Instead of designing a model compression
algorithm with a high compression ratio, MoTransFrame can transplant popular convolutional
neural networks models to resources-starved edge devices promptly and More >
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