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Automatic Modulation Classification Using Hybrid Data Augmentation and Lightweight Neural Network
Sensors, 2023 Automatic modulation classification (AMC) plays an important role in intelligent wireless communications. With the rapid development of deep learning in recent years, neural network-based automatic modulation classification methods have become ...
Fan Wang +3 more
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Design and Implementation of Accelerator for Lightweight Neural Network [PDF]
Jisuanji gongcheng, 2021 This paper designs a network accelerator based on the Field Programmable Gate Array(FPGA) platform for the lightweight convolutional network represented by MobileNet.By optimizing DW and PW lightweight modules and implementing commonly used convolution ...
HUANG Rui, JIN Guanghao, LI Lei, JIANG Wenchao, SONG Qingzeng
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Survey of Research on Lightweight Neural Network Structures for Deep Learning [PDF]
Jisuanji gongcheng, 2021 With the rapid development of deep neural networks and smart mobile devices, the research of lightweight neural network structure has gradually become a hotspot.
WANG Jun, FENG Suncheng, CHENG Yong
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Research Progress of Lightweight Neural Network Convolution Design [PDF]
Jisuanji kexue yu tansuo, 2022 Traditional neural networks have the disadvantages of over-reliance on hardware resources and high requirements for application equipment performance. Therefore, they cannot be deployed on edge devices and mobile terminals with limited computing power ...
MA Jinlin, ZHANG Yu, MA Ziping, MAO Kaiji
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Face Detection Algorithm Based on Lightweight Convolutional Neural Network [PDF]
Jisuanji gongcheng, 2021 When deployed to mobile terminals,face detection applications are usually limited by the computing power and storage resources of the devices.To address the problem,an improved face detection algorithm called Lightweight-SSH using lightweight ...
ZHU Lingling, GAO Chao, CHEN Fucai
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Improved Dual-Channel Attention Mechanism Image Classification Method for Lightweight Network [PDF]
Hangkong bingqi, 2021 In order to solve the problems of large volume and high hardware requirements of deep convolutional neural network model in missile-borne terminal environment, a lightweight network structure based on improved dual-channel attention mechanism is ...
Song Tainian, Qin Weiwei, Liang Zhuo, Wang Kui, Liu Gang
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Lightweight Security for Network Coding [PDF]
2008 IEEE International Conference on Communications, 2008 Under the emerging network coding paradigm, intermediate nodes in the network are allowed not only to store and forward packets but also to process and mix different data flows. We propose a low-complexity cryptographic scheme that exploits the inherent security provided by random linear network coding and offers the advantage of reduced overhead in ...
João P. Vilela +2 more
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Research on Deep Learning Network Compression Method for Missile Borne Image [PDF]
Hangkong bingqi, 2023 Aiming at the problem that the target recognition algorithm based on deep learning has the characteristics of complex network structure, large amount of parameters and high computation delay, which is difficult to directly apply to the missile-borne task,
Gao Yibo, Yang Chuandong, Chen Dong, Ling Chong
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IET Computer Vision, 2022 Despite their success, existing human pose estimation approaches mostly have complex architectures, high cost, and lack of lightweight modules. To address this problem, this paper proposes a Ghost Shuffle Lightweight Pose Network (GSLPN) with a more ...
Senquan Yang, Jiajun Wen, Junjun Fan
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Lightweight Coloring and Desynchronization for Networks [PDF]
IEEE INFOCOM 2009, 2009 We study the distributed desynchronization problem for graphs with arbitrary topology. Motivated by the severe computational limitations of sensor networks, we present a randomized algorithm for network desynchronization that uses an extremely lightweight model of computation, while being robust to link volatility and node failure.
Arik Motskin +3 more
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