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Classification network and implementation method and device thereof

A technology of classification network and implementation method, which is applied in the field of neural network, can solve the problems of high complexity of classification network and large memory usage, and achieve the effects of improving training efficiency, simplifying network structure and saving manpower

Pending Publication Date: 2021-05-07
GOERTEK INC
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Problems solved by technology

However, the classification network based on the IRv2 algorithm also has problems such as high complexity and large memory usage, which need to be solved urgently

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  • Classification network and implementation method and device thereof
  • Classification network and implementation method and device thereof
  • Classification network and implementation method and device thereof

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Embodiment Construction

[0027] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with specific embodiments of the present application and corresponding drawings. Apparently, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0028] In order to expand the applicable scenarios of the classification neural network, reduce the training and reasoning time of the classification neural network, and compress the model size of the classification neural network, a large number of pruning, compression and quantization methods have been proposed in the academic community. Pruning, co...

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Abstract

The invention discloses a classification network and an implementation method and device thereof, and the method comprises the steps: constructing a classification network which comprises a Stem module, a plurality of Inception modules and a plurality of IR modules based on an IRv2 algorithm, wherein a batch standardization BN layer of the classification network uses a gamma parameter; initializing the classification network, and performing sparse training on the initialized classification network to obtain a sparse gamma parameter; on the basis of the sparse gamma parameter, carrying out the network slip pruning on the Stem module, the pruning Inception module and the plurality of IR modules, wherein network slip pruning is not carried out on the non-pruning Inception module. According to the technical scheme, the classification effect of the classification network can be ensured, and meanwhile, simplification of a network structure is realized, so the training efficiency is improved, the reasoning time and memory occupation are reduced, manpower, working hours and funds are saved, and the classification network can be deployed on hardware equipment with different computing power.

Description

technical field [0001] The present application relates to the technical field of neural networks, in particular to a classification network and its implementation method and device. Background technique [0002] The full name of the IRv2 algorithm is Inception-ResNet-v2, which is the second generation algorithm that combines Inception and ResNet (residual network) for classification. Combining the advantages of Inception and ResNet, it can obtain a deeper classification network and better classification performance. very good. However, the classification network based on the IRv2 algorithm also has problems such as high complexity and large memory usage, which need to be solved urgently. Contents of the invention [0003] The embodiment of the present application provides a classification network and its implementation method and device, which can not only ensure the classification effect of the classification network, but also reduce the complexity of the classification ...

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/047G06N3/045G06F18/2415
Inventor 冯蓬勃张一凡刘杰
Owner GOERTEK INC
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