Machine Learning and IoT for Intelligent Systems and Smart Applications

Machine Learning and IoT for Intelligent Systems and Smart Applications

Kumar, M Vinoth; P, Madhumathy; Umamaheswari, R.

Taylor & Francis Ltd

10/2024

228

Mole

9781032047256

Pré-lançamento - envio 15 a 20 dias após a sua edição

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Chapter 1 A Study on Feature Extraction and Classification Techniques for Melanoma Detection

Chapter 2 Machine Learning based Microstrip Antenna Design in Wireless Communications

Chapter 3 LCL-T Filter Based Analysis of Two Stage Single Phase Grid Connected Module with Intelligent FANN Controllers

Chapter 4 Motion Vector Analysis Using Machine Learning Models to Identify Lung Damages for COVID-19 Patients

Chapter 5 Enhanced Effective Generative Adversarial Networks Based LRSD and SP Learned Dictionaries with Amplifying CS

Chapter 6 Deep Learning Based Parkinson's Disease Prediction System

Chapter 7 Non-Uniform Data Reduction Technique with Edge Preservation to Improve Diagnostic Visualization of Medical Images

Chapter 8 A Critical Study on Genetically Engineered Bioweapons and Computer-Based Techniques as Counter Measure

Chapter 9 An Automated Hybrid Transfer Learning system for Detection and Segmentation of Tumor in MRI Brain Images with UNet and VGG-19 Network

Chapter 10 Deep Learning-Computer Aided Melanoma Detection Using Transfer Learning

Chapter 11 Development of an Agent-based Interactive Tutoring System for Online Teaching in School using Classter

Chapter 12 Fusion of Datamining and Artificial Intelligence in Prediction of Hazardous Road Accidents
UPDRS Score;Ultrasound Signals;LCL Filter;Image Processing;Mri Image;Wireless Communication;SVM Classifier;Neuro-Fuzzy;Dermoscopic Images;Neural Networks;Wavelet Transform;Covid;Multimodal Mri;Motor UPDRS Score;Total UPDRS Score;Mri Brain Image;RBM;Ultrasound Video;Data Reduction Algorithm;RF Classification Model;Non-subsampled Contourlet Transform;Sub-band Coefficients;Parabolic Scaling;Computer Assisted Surgery;Curvelet Transform;Supervised Machine Learning;MV;Mri Dataset;Total Harmonic Distortion;UCI Dataset;SP Module