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Herausgeber: 
  • Deepak Gupta
  • Ram Bilas Pachori
  • M. Tanveer
  • Rajat Subhra Goswami
  • Subhasish Banerjee
  • Pattern Recognition and Data Analysis with Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  September 2022  
    Genre:  Naturwissensch., Medizin, Technik 
     
    BigDataAnalytics / Computerhardware / Computervision / Datenbanken / Datenmanagement / Digitale Signalverarbeitung (DSP) / kerneldesign / Künstliche Intelligenz (KI) / MachineLearningandApplications
    ISBN:  9789811915192 
    EAN-Code: 
    9789811915192 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 241 mm / B 160 mm / D 51 mm 
    Gewicht:  1431 gr 
    Seiten:  856 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book covers latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing and their applications in real world. The topics covered in machine learning involves feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN) and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modelling from video, 3D object recognition, localization and tracking, medical image analysis and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multi-task, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with theintegration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG) and electromyogram (EMG).

      



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