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 aerial vehi...
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| Autores principales: | , , , |
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| Formato: | Online |
| Lenguaje: | inglés |
| Publicado: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Materias: | |
| Acceso en línea: | 46102 |
| Etiquetas: |
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| _version_ | 1863734560873775104 |
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| author | Kung, Hsu-Yang Chen, Chi-Hua Horng, Mong-Fong Hwang, Feng-Jang |
| author_browse | Chen, Chi-Hua Horng, Mong-Fong Hwang, Feng-Jang Kung, Hsu-Yang |
| author_facet | Kung, Hsu-Yang Chen, Chi-Hua Horng, Mong-Fong Hwang, Feng-Jang |
| author_sort | Kung, Hsu-Yang |
| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-44630 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-446302024-04-11T15:11:33Z Deep Learning Applications with Practical Measured Results in Electronics Industries Kung, Hsu-Yang Chen, Chi-Hua Horng, Mong-Fong Hwang, Feng-Jang TA1-2040 T1-995 faster region-based CNN visual tracking intelligent tire manufacturing eye-tracking device neural networks A* information measure oral evaluation GSA-BP tire quality assessment humidity sensor rigid body kinematics intelligent surveillance residual networks imaging confocal microscope update mechanism multiple linear regression geometric errors correction data partition Imaging Confocal Microscope image inpainting lateral stage errors dot grid target K-means clustering unsupervised learning recommender system underground mines digital shearography optimization techniques saliency information gated recurrent unit multivariate time series forecasting multivariate temporal convolutional network foreign object data fusion update occasion generative adversarial network CNN compressed sensing background model image compression supervised learning geometric errors UAV nonlinear optimization reinforcement learning convolutional network neuro-fuzzy systems deep learning image restoration neural audio caption hyperspectral image classification neighborhood noise reduction GA MCM uncertainty evaluation binary classification content reconstruction kinematic modelling long short-term memory transfer learning network layer contribution instance segmentation smart grid unmanned aerial vehicle forecasting trajectory planning discrete wavelet transform machine learning computational intelligence tire bubble defects offshore wind multiple constraints human computer interaction Least Squares method thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology 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. 2021-02-11T11:03:13Z 2021-02-11T11:03:13Z 2020-06-09 16:38:57 2020 book 46102 9783039288649 9783039288632 https://directory.doabooks.org/handle/20.500.12854/44630 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/2296 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03928-864-9 10.3390/books978-3-03928-864-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039288649 9783039288632 272 open access |
| spellingShingle | TA1-2040 T1-995 faster region-based CNN visual tracking intelligent tire manufacturing eye-tracking device neural networks A* information measure oral evaluation GSA-BP tire quality assessment humidity sensor rigid body kinematics intelligent surveillance residual networks imaging confocal microscope update mechanism multiple linear regression geometric errors correction data partition Imaging Confocal Microscope image inpainting lateral stage errors dot grid target K-means clustering unsupervised learning recommender system underground mines digital shearography optimization techniques saliency information gated recurrent unit multivariate time series forecasting multivariate temporal convolutional network foreign object data fusion update occasion generative adversarial network CNN compressed sensing background model image compression supervised learning geometric errors UAV nonlinear optimization reinforcement learning convolutional network neuro-fuzzy systems deep learning image restoration neural audio caption hyperspectral image classification neighborhood noise reduction GA MCM uncertainty evaluation binary classification content reconstruction kinematic modelling long short-term memory transfer learning network layer contribution instance segmentation smart grid unmanned aerial vehicle forecasting trajectory planning discrete wavelet transform machine learning computational intelligence tire bubble defects offshore wind multiple constraints human computer interaction Least Squares method thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Kung, Hsu-Yang Chen, Chi-Hua Horng, Mong-Fong Hwang, Feng-Jang Deep Learning Applications with Practical Measured Results in Electronics Industries |
| title | Deep Learning Applications with Practical Measured Results in Electronics Industries |
| title_full | Deep Learning Applications with Practical Measured Results in Electronics Industries |
| title_fullStr | Deep Learning Applications with Practical Measured Results in Electronics Industries |
| title_full_unstemmed | Deep Learning Applications with Practical Measured Results in Electronics Industries |
| title_short | Deep Learning Applications with Practical Measured Results in Electronics Industries |
| title_sort | deep learning applications with practical measured results in electronics industries |
| topic | TA1-2040 T1-995 faster region-based CNN visual tracking intelligent tire manufacturing eye-tracking device neural networks A* information measure oral evaluation GSA-BP tire quality assessment humidity sensor rigid body kinematics intelligent surveillance residual networks imaging confocal microscope update mechanism multiple linear regression geometric errors correction data partition Imaging Confocal Microscope image inpainting lateral stage errors dot grid target K-means clustering unsupervised learning recommender system underground mines digital shearography optimization techniques saliency information gated recurrent unit multivariate time series forecasting multivariate temporal convolutional network foreign object data fusion update occasion generative adversarial network CNN compressed sensing background model image compression supervised learning geometric errors UAV nonlinear optimization reinforcement learning convolutional network neuro-fuzzy systems deep learning image restoration neural audio caption hyperspectral image classification neighborhood noise reduction GA MCM uncertainty evaluation binary classification content reconstruction kinematic modelling long short-term memory transfer learning network layer contribution instance segmentation smart grid unmanned aerial vehicle forecasting trajectory planning discrete wavelet transform machine learning computational intelligence tire bubble defects offshore wind multiple constraints human computer interaction Least Squares method thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | TA1-2040 T1-995 faster region-based CNN visual tracking intelligent tire manufacturing eye-tracking device neural networks A* information measure oral evaluation GSA-BP tire quality assessment humidity sensor rigid body kinematics intelligent surveillance residual networks imaging confocal microscope update mechanism multiple linear regression geometric errors correction data partition Imaging Confocal Microscope image inpainting lateral stage errors dot grid target K-means clustering unsupervised learning recommender system underground mines digital shearography optimization techniques saliency information gated recurrent unit multivariate time series forecasting multivariate temporal convolutional network foreign object data fusion update occasion generative adversarial network CNN compressed sensing background model image compression supervised learning geometric errors UAV nonlinear optimization reinforcement learning convolutional network neuro-fuzzy systems deep learning image restoration neural audio caption hyperspectral image classification neighborhood noise reduction GA MCM uncertainty evaluation binary classification content reconstruction kinematic modelling long short-term memory transfer learning network layer contribution instance segmentation smart grid unmanned aerial vehicle forecasting trajectory planning discrete wavelet transform machine learning computational intelligence tire bubble defects offshore wind multiple constraints human computer interaction Least Squares method thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | 46102 |
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