LEADER 03193nam 2200481 450 001 9910484944303321 005 20210225155413.0 010 $a981-15-6759-X 024 7 $a10.1007/978-981-15-6759-9 035 $a(CKB)4100000011469474 035 $a(MiAaPQ)EBC6357258 035 $a(DE-He213)978-981-15-6759-9 035 $a(PPN)25021900X 035 $a(EXLCZ)994100000011469474 100 $a20210225d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDeep learning applications$hVolume 2 /$fM. Arif Wani, Taghi M. Khoshgoftaar, Vasile Palade, editors 205 $a1st ed. 2021. 210 1$aGateway East, Singapore :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (XII, 300 p. 128 illus., 108 illus. in color.) 225 1 $aAdvances in Intelligent Systems and Computing,$x2194-5357 ;$v1232 311 $a981-15-6758-1 327 $aDeep Learning Based Recommender Systems -- A Comprehensive Set of Novel Residual Blocks for Deep Learning Architectures for Diagnosis of Retinal Diseases from Optical Coherence Tomography Images -- Three-Stream Convolutional Neural Network for Human Fall Detection -- Diagnosis of Bearing Faults in Electrical Machines using Long Short-Term Memory -- Automatic Solar Panel Detection from High Resolution Orthoimagery Using Deep Learning Segmentation Networks -- Training Deep Learning Sequence Models to Understand Driver Behavior -- Exploiting Spatio-temporal Correlation in RF Data using Deep Learning -- Human Target Detection and Localization with Radars Using Deep Learning -- Thresholding Strategies for Deep Learning with Highly Imbalanced Big Data -- Vehicular Localisation at High and Low Estimation Rates during GNSS Outages: A Deep Learning Approach -- Multi-Adversarial Variational Autoencoder Nets for Simultaneous Image Generation and Classification -- Non-convex Optimization using Parameter Continuation Methods for Deep Neural Networks. 330 $aThis book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. 410 0$aAdvances in Intelligent Systems and Computing,$x2194-5357 ;$v1232 606 $aMachine learning$vCongresses 615 0$aMachine learning 676 $a006.31 702 $aWani$b M. A$g(M. Arif), 702 $aKhoshgoftaar$b Taghi M. 702 $aPalade$b Vasile$f1964- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484944303321 996 $aDeep Learning Applications$92823910 997 $aUNINA