Deep Learning Applications with Practical Measured Results in Electronics Industries
This book collects 14 articles from the Special Issue entitled "Deep Learning Applications with Practical Measured Results in Electronics Industries" of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned a...
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Other Authors: | , , |
Format: | Electronic Book Chapter |
Language: | English |
Published: |
MDPI - Multidisciplinary Digital Publishing Institute
2020
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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Summary: | This book collects 14 articles from the Special Issue entitled "Deep Learning Applications with Practical Measured Results in Electronics Industries" of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods. |
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Physical Description: | 1 electronic resource (272 p.) |
ISBN: | books978-3-03928-864-9 9783039288649 9783039288632 |
Access: | Open Access |