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020			_a9789811513664
024	7		_a10.1007/978-981-15-1366-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA347 .A78 _b2020 EB
245	0	0	_aMachine Intelligence and Signal Processing : _bProceedings of International Conference, MISP 2019 _cedited by Sonali Agarwal, Shekhar Verma, Dharma P. Agrawal.
250			_aFirst edition 2020.
264		1	_aSingapore _bSpringer Singapore : _bImprint: Springer _c2020.
300			_a1 recurso en línea (XVI, 466 páginas) _b244 ilustraciones, 168 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aAdvances in Intelligent Systems and Computing _x2194-5357 _v1085
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aRing 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.
520	3		_aThis 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).
988			_aSpringer_Robotics_31032020
650		7	_2embne _aInteligencia artificial _vCongresos y asambleas _9413115
700	1		_aAgarwal, Sonali _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aVerma, Shekhar _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aAgrawal, Dharma P _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
776	0	8	_iPrinted edition: _z9789811513657
776	0	8	_iPrinted edition: _z9789811513671
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-1366-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2020 _dz _eh _zSI