Zero-Centered Fixed-Point Quantization With Iterative Retraining for Deep Convolutional Neural Network-Based Object Detectors

Zero-Centered Fixed-Point Quantization With Iterative Retraining for Deep Convolutional Neural Network-Based Object Detectors

In the field of object detection, deep learning has greatly improved accuracy compared to previous algorithms and has been used widely in recent years. However, object detection using deep learning requires many hardware (HW) resources due to the huge computations for high performance, making it ver...

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Bibliographic Details
Main Authors: Sungrae Kim, Hyun Kim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
deep neural network
fixed-point quantization
network compression
object detector
YOLOv3
Online Access:https://ieeexplore.ieee.org/document/9336635/

Internet

https://ieeexplore.ieee.org/document/9336635/

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