基于云边协同的计算机视觉推理机制

doi:10.11959/j.issn.1000-0801.2021107

Abstract

Abstract:

The popularity of deep learning and cloud computing has promoted the widespread application of computer vision in various industries.However, centralized cloud inference services have problems such as high bandwidth resource consumption, image data privacy leakage, and high latency.It is hard that satisfy demand which requires diversified computer vision application.The dual gigabit upgrade of the communication network will promote depth collaboration of computer vision cloud-edge algorithms.Aiming to study the computer vision inference mechanism based on cloud-edge collaboration.Firstly, the advantages and disadvantages of the mainstream cloud and edge computer vision inference models in recent years were analyzed and explained, and on this basis, research on the cloud-edge collaborative computer vision inference model framework and deployment mechanism was carried out, model distributed reasoning model segmentation strategy, cloud-side collaborative network deployment optimization strategy was discussed in detail.In the end, the challenge and prospect of deep learning cloud-edge collaboration inference in future was discussed through data collaboration, network partition collaboration, and business function collaboration .

Key words: computer vision, deep learning,, cloud-edge collaboration

CLC Number:

TP393

Boheng TANG, Xingang CHAI. Cloud-edge collaboration based computer vision inference mechanism[J]. Telecommunications Science, 2021, 37(5): 72-81.

Figures/Tables 3

References 46

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网络名称	网络深度	参数数量/MB	浮点运算数量/10⁹次	Top1错误率
AlexNet	8	61	1.45	36.7%
VGG16	16	138	31.0	25.6%
Inception-v1	22	5	2.86	30.2%
Inception-v2	42	11	4.0	25.2%
Inception-v3	48	24	11.4	21.2%
Inception-v4	76	35	24.5	19.9%
ResNet-152	152	60	22.6	19.4%
ResNeXt	50	68	8.4	19.1%
DenseNet	201	20	8.4	13.6%

Cloud-edge collaboration based computer vision inference mechanism

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