Collaborative Inference Method Using Optimal Confidence Thresholds in Intelligent Surveillance Systems 


Vol. 50,  No. 2, pp. 253-256, Feb.  2025
10.7840/kics.2025.50.2.253


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  Abstract

This study proposes a novel collaborative inference method between edge device and edge server for intelligent surveillance services. In the proposed method, the device uses a small neural network (NN) and filters ambiguous input images by setting two confidence thresholds. These filtered images are then forwarded to the edge server for re-evaluation with a larger NN. Simulation results show that the proposed collaborative inference method, using optimal confidence thresholds, significantly reduces latency while meeting the required accuracy.

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[IEEE Style]

H. Choi, "Collaborative Inference Method Using Optimal Confidence Thresholds in Intelligent Surveillance Systems," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 2, pp. 253-256, 2025. DOI: 10.7840/kics.2025.50.2.253.

[ACM Style]

Hyun-Ho Choi. 2025. Collaborative Inference Method Using Optimal Confidence Thresholds in Intelligent Surveillance Systems. The Journal of Korean Institute of Communications and Information Sciences, 50, 2, (2025), 253-256. DOI: 10.7840/kics.2025.50.2.253.

[KICS Style]

Hyun-Ho Choi, "Collaborative Inference Method Using Optimal Confidence Thresholds in Intelligent Surveillance Systems," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 2, pp. 253-256, 2. 2025. (https://doi.org/10.7840/kics.2025.50.2.253)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880