FPGA-Based Hybrid-Type Implementation of Quantized Neural Networks for Remote Sensing Applications

FPGA-Based Hybrid-Type Implementation of Quantized Neural Networks for Remote Sensing Applications

Recently, extensive convolutional neural network (CNN)-based methods have been used in remote sensing applications, such as object detection and classification, and have achieved significant improvements in performance. Furthermore, there are a lot of hardware implementation demands for remote sensi...

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Bibliographic Details
Main Authors: Xin Wei, Wenchao Liu, Lei Chen, Long Ma, He Chen, Yin Zhuang
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Sensors
Subjects:
remote sensing
convolutional neural network
hybrid-type inference
symmetric quantization
FPGA
Online Access:https://www.mdpi.com/1424-8220/19/4/924

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