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Hardware-Aware Zero-Shot Neural Architecture Search | IEEE Conference Publication | IEEE Xplore

Hardware-Aware Zero-Shot Neural Architecture Search


Abstract:

Designing a convolutional neural network architecture that achieves low-latency and high accuracy on edge devices with constrained computational resources is a difficult ...Show More

Abstract:

Designing a convolutional neural network architecture that achieves low-latency and high accuracy on edge devices with constrained computational resources is a difficult challenge. Neural architecture search (NAS) is used to optimize the architecture in a large design space, but at huge computational cost. As a countermeasure, we use here the zero-shot NAS method. A drawback to the previous method was that a discrepancy of correction occurred between the evaluation score of the neural architecture and its accuracy. To address this problem, we refined the neural architecture search space from previous zero-shot NAS. The neural architecture obtained using the proposed method achieves ImageNet top-1 accuracy of 75.3% under conditions of latency equivalent to MobileNetV2 (ImageNet top-1 accuracy is 71.8%) on the Qualcomm SA8155 platform.
Date of Conference: 23-25 July 2023
Date Added to IEEE Xplore: 22 August 2023
ISBN Information:
Conference Location: Hamamatsu, Japan

References

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