A Fully 4-bit Quantized MobileNet-SSD

Quantizing the detector is more challenging than the classifier; consequently, previous studies used some layers as floating-point layers. This leads to the problem that quantized detectors cannot be accelerated in integer-only operating devices. In this study, we present a fully 4-bit quantized MobileNet-SSD. Furthermore, we propose an optimized weight freezing order and a Knowledge Distillation (KD) loss function to minimize accuracy degradation. Our detector achieves mAP 65.09% in PASCAL VOC, which is 0.63 points higher than prior work, and we conducted detailed experiments about the proposed KD loss function.

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Publication Details

Published
2024-08-19
DOI
https://doi.org/10.1109/isocc62682.2024.10762576
Primary Topic
Advanced Data Storage Technologies
Type
article
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article

A Fully 4-bit Quantized MobileNet-SSD

Sang-Seol Lee, Minkyu Lee, Eunchong Lee, Yu-Mi Kim et al.
Advanced Data Storage Technologies
article

A Fully 4-bit Quantized MobileNet-SSD

Sang-Seol Lee, Minkyu Lee, Eunchong Lee, Yu-Mi Kim, Aeri Kim
article en

Abstract

Quantizing the detector is more challenging than the classifier; consequently, previous studies used some layers as floating-point layers. This leads to the problem that quantized detectors cannot be accelerated in integer-only operating devices. In this study, we present a fully 4-bit quantized MobileNet-SSD. Furthermore, we propose an optimized weight freezing order and a Knowledge Distillation (KD) loss function to minimize accuracy degradation. Our detector achieves mAP 65.09% in PASCAL VOC, which is 0.63 points higher than prior work, and we conducted detailed experiments about the proposed KD loss function.

Korea Electronics Technology Institute (KR)
Openalex Percentile: Top 75%
Advanced Data Storage Technologies
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