05024nam 2201249z- 450 9910404080403321202102113-03928-864-4(CKB)4100000011302334(oapen)https://directory.doabooks.org/handle/20.500.12854/44630(oapen)doab44630(EXLCZ)99410000001130233420202102d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierDeep Learning Applications with Practical Measured Results in Electronics IndustriesMDPI - Multidisciplinary Digital Publishing Institute20201 online resource (272 p.)3-03928-863-6 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.History of engineering and technologybicsscA*background modelbinary classificationCNNcompressed sensingcomputational intelligencecontent reconstructionconvolutional networkdata fusiondata partitiondeep learningdigital shearographydiscrete wavelet transformdot grid targeteye-tracking devicefaster region-based CNNforecastingforeign objectGAgated recurrent unitgenerative adversarial networkgeometric errorsgeometric errors correctionGSA-BPhuman computer interactionhumidity sensorhyperspectral image classificationimage compressionimage inpaintingimage restorationimaging confocal microscopeImaging Confocal Microscopeinformation measureinstance segmentationintelligent surveillanceintelligent tire manufacturingK-means clusteringkinematic modellinglateral stage errorsLeast Squares methodlong short-term memorymachine learningMCM uncertainty evaluationmultiple constraintsmultiple linear regressionmultivariate temporal convolutional networkmultivariate time series forecastingneighborhood noise reductionnetwork layer contributionneural audio captionneural networksneuro-fuzzy systemsnonlinear optimizationoffshore windoptimization techniquesoral evaluationrecommender systemreinforcement learningresidual networksrigid body kinematicssaliency informationsmart gridsupervised learningtire bubble defectstire quality assessmenttrajectory planningtransfer learningUAVunderground minesunmanned aerial vehicleunsupervised learningupdate mechanismupdate occasionvisual trackingHistory of engineering and technologyKung Hsu-Yangauth1328954Chen Chi-HuaauthHorng Mong-FongauthHwang Feng-JangauthBOOK9910404080403321Deep Learning Applications with Practical Measured Results in Electronics Industries3039220UNINA