A Fast Indoor Positioning Using a Knowledge-Distilled Convolutional Neural Network (KD-CNN)
Author:
Affiliation:
1. Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia
2. School of Information Technology, Monash University Malaysia, Subang Jaya, Malaysia
Funder
Fundamental Research Grant Scheme (FRGS), Ministry of Higher Education Malaysia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09795287.pdf?arnumber=9795287
Reference34 articles.
1. Distilling the knowledge in a neural network;hinton;Proc Deep Learn Represent Learn Workshop (NIPS),2015
2. Deep CNN for Indoor Localization in IoT-Sensor Systems
3. Mixed Pooling for Convolutional Neural Networks
4. Improving Fingerprint Indoor Localization Using Convolutional Neural Networks
5. Inplace knowledge distillation with teacher assistant for improved training of flexible deep neural networks
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