Efficient and Small Network Using Multi-Trim Network Structure for Tactile Object Recognition on Embedded Systems

Efficient and Small Network Using Multi-Trim Network Structure for Tactile Object Recognition on Embedded Systems

Tactile object recognition (TOR) is critical in robot perception. However, as an embedded system, a robot brain has a fixed resource budget and is unsuitable for modern convolutional neural networks (CNNs). To bridge this gap, we present a simple network-compression approach that improves the accura...

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Bibliographic Details
Main Authors: Pornthep Sarakon, Hideaki Kawano, Kazuhiro Shimonomura, Seiichi Serikawa
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Image classification
convolutional neural network
network compression
embedded system
tactile sensor
Online Access:https://ieeexplore.ieee.org/document/9162040/

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