Machine Intelligence and Signal Processing : Proceedings of International Conference, MISP 2019 / / edited by Sonali Agarwal, Shekhar Verma, Dharma P. Agrawal

• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020
• Edizione: 1st ed. 2020.
• Descrizione fisica: 1 online resource (464 pages) : color illustrations
• Disciplina: 006.3
• Soggetto topico: Computational intelligence; Signal processing; Computer networks; Electric power production; Computational Intelligence; Signal, Speech and Image Processing; Computer Communication Networks; Electrical Power Engineering
• Persona (resp. second.): AgarwalSonali; VermaShekhar; AgrawalDharma P
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Ring Partition Based Fingerprint Indexing Algorithm -- A Novel Approach for Music Recommendation System using Matrix Factorization Technique -- Generation of Image Captions using VGG and ResNet CNN Models Cascaded with RNN Approach -- Face Classification across Pose by Using Non-Linear Regression and Discriminatory Face Information -- Emotion Recognition from Facial Images for Tamil Language Speakers -- A Phase Noise Correction Scheme for Multi-channel Multi-echo SWI processing -- A Scanning Technique based on Selective Neighbour Channels in 802.11 Wi-Fi Networks -- Persistent Homology Techniques for Big Data and Machine Intelligence: A survey -- Concave Point Extraction: A Novel Method for WBC Segmentation in ALL Images -- Speech Emotion Recognition for Tamil Language Speakers -- Real Time RADAR and LIDAR Sensor Fusion for Automated Driving -- Generalizing Streaming Pipeline Design for Big - Data -- Adaptive Fast Composite Splitting Algorithm for MR Image Reconstruction -- Extraction of Technical and Non-technical skills for Optimal Project-Team Allocation -- Modified Flower Pollination Algorithm for Optimal Power Flow in Transmission Congestion -- Intelligent Condition Monitoring of a CI Engine Using Machine Learning and Artificial Neural Networks -- Bacterial Foraging Optimization in Non-identical Parallel Batch Processing Machines -- Healthcare Information Retrieval based on Neutrosophic Logic -- Convolutional Neural Network Long Short-Term Memory (CNN+LSTM) for Histopathology Cancer Image Classification -- Forecasting with Multivariate Fuzzy Time Series: A Statistical Approach -- Nature-Inspired Algorithm-Based Feature Optimization for Epilepsy Detection -- A Combined Machine-Learning Approach for Accurate Screening and Early Detection of Chronic Kidney Disease -- Backpropagation and Self Organizing Map Neural Network Methods for Identifying Types of Eggplant Fruit -- Head Pose Prediction while Tracking Lost in a Head Mounted Display -- Recommendation to Group of Users using The Relevance Concept -- ACA: Attention based Context-aware Answer selection system -- Dense and Partial Correspondence in Non-Parametric Scene Parsing -- Audio Surveillance System -- MOPSA: Multiple Output Prediction for Scalability and Accuracy -- Impact of Cluster Sampling on the Classification of Landsat-8 Remote Sensing Imagery -- Deep Neural Networks for Out-Of-Sample Classification of Non-Linear Manifolds -- FPGA implementation of LDPC Decoder -- A Multiclass Classi_cation of Epileptic Activity in Patients using Wavelet Decomposition -- Hexa-Directional Feature Extraction for Target-Specific Handwritten Digit Recognition -- Cardiovascular Disease Prediction using Machine Learning Tools -- Analysis of Global Motion Compensation and Polar Vector Median for Object Tracking Using St-MRF In Video Surveillance.
• Sommario/riassunto: This book features selected high-quality research papers presented at the International Conference on Machine Intelligence and Signal Processing (MISP 2019), held at the Indian Institute of Technology, Allahabad, India, on September 7–10, 2019. The book covers the latest advances in the fields of machine learning, big data analytics, signal processing, computational learning theory, and their real-time applications. The topics covered include support vector machines (SVM) and variants like least-squares SVM (LS-SVM) and twin SVM (TWSVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. Further, it discusses the real-time challenges involved in processing big data and adapting the algorithms dynamically to improve the computational efficiency. Lastly, it describes recent developments in processing signals, for instance, signals generated from IoT devices, smart systems, speech, and videos and addresses biomedical signal processing: electrocardiogram (ECG) and electroencephalogram (EEG).
• Titolo autorizzato: Machine Intelligence and Signal Processing
• ISBN: 981-15-1366-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910484297703321
• Lo trovi qui: Univ. Federico II
• Serie: Advances in Intelligent Systems and Computing, . 2194-5365 ; ; 1085