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• Introduction
• Fundamentals of Machine Learning
• Perceptrons
• Multilayer perceptrons: architecture and error backpropagation
• Multilayer perceptrons: other learing techniques
• Hopfield networks, simulated annealing and chaotic neural networks
• Associative memory networks
• Clustering I: Basic clustering models and algorithms
• Clustering II: topics in clustering
• Radial basis function networks
• Recurrent neural networks
• Principal component analysis
• Nonnegative matrix factorization and compressed sensing
• Independent component analysis
• Discriminant analysis
• Support vector machines
• Other kernel methods
• Reinforcement learning
• Probabilistic and Bayesian networks
• Combining multiple learners: data fusion and emsemble learning
• Introduction of fuzzy sets and logic
• Neurofuzzy systems
• Neural circuits
• Pattern recognition for biometrics and bioinformatics
• Data mining.

This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: " multilayer perceptron; " the Hopfield network; " associative memory models; " clustering models and algorithms; " t he radial basis function network; " recurrent neural networks; " nonnegative matrix factorization; " independent component analysis; " robabilistic and Bayesian networks; and " fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning

• Preface.- Introduction.- Simulated Annealing.- Optimization by Recurrent Neural Networks.- Genetic Algorithms and Genetic Programming.- Evolutionary Strategies.- Differential Evolution.- Estimation of Distribution Algorithms.- Mimetic Algorithms.- Topics in EAs.- Particle Swarm Optimization.- Artificial Immune Systems.- Ant Colony Optimization.- Tabu Search and Scatter Search.- Bee Metaheuristics.- Harmony Search.- Biomolecular Computing.- Quantum Computing.- Other Heuristics-Inspired Optimization Methods.- Dynamic, Multimodal, and Constraint-Satisfaction Optimizations.- Multiobjective Optimization.-
• Appendix 1: Discrete Benchmark Functions.-
• Appendix 2: Test Functions.- Index.
• (source: Nielsen Book Data)

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.
(source: Nielsen Book Data)

• Introduction.- Fundamentals of Machine Learning.- Perceptrons.- Multilayer perceptrons: architecture and error backpropagation.- Multilayer perceptrons: other learing techniques.- Hopfield networks, simulated annealing and chaotic neural networks.- Associative memory networks.- Clustering I: Basic clustering models and algorithms.- Clustering II: topics in clustering.- Radial basis function networks.- Recurrent neural networks.- Principal component analysis.- Nonnegative matrix factorization and compressed sensing.- Independent component analysis.- Discriminant analysis.- Support vector machines.- Other kernel methods.- Reinforcement learning.- Probabilistic and Bayesian networks.- Combining multiple learners: data fusion and emsemble learning.- Introduction of fuzzy sets and logic.- Neurofuzzy systems.- Neural circuits.- Pattern recognition for biometrics and bioinformatics.- Data mining.- Appenidx A. Mathematical Preliminaries.- Appendix B. Benchmarks and resources.
• (source: Nielsen Book Data)

Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.
(source: Nielsen Book Data)

• 1. Introduction
• 2. An overview of wireless communications
• 3. Channel and propagation
• 4. Cellular and multiple-user systems
• 5. Diversity
• 6. Channel estimation and equalization
• 7. Modulation and detection
• 8. Spread spectrum communications
• 9. Orthogonal frequency division multiplexing
• 10. Antennas
• 11. RF and microwave subsystems
• 12. A/D and D/A conversions
• 13. Signals and signal processing
• 14. Fundamentals of information theory
• 15. Channel coding
• 16. Source coding I: speech and audio coding
• 17. Source coding II: image and video coding
• 18. Multiple antennas: smart antenna systems
• 19. Multiple antennas: MIMO systems
• 20. Ultra wideband communications
• 22. Wireless ad hoc/sensor networks
• The Q-function
• Wirtinger calculus.
• (source: Nielsen Book Data)

This practically-oriented, all-inclusive guide covers all the major enabling techniques for current and next-generation cellular communications and wireless networking systems. Technologies covered include CDMA, OFDM, UWB, turbo and LDPC coding, smart antennas, wireless ad hoc and sensor networks, MIMO, and cognitive radios, providing readers with everything they need to master wireless systems design in a single volume. Uniquely, a detailed introduction to the properties, design, and selection of RF subsystems and antennas is provided, giving readers a clear overview of the whole wireless system. It is also the first textbook to include a complete introduction to speech coders and video coders used in wireless systems. Richly illustrated with over 400 figures, and with a unique emphasis on practical and state-of-the-art techniques in system design, rather than on the mathematical foundations, this book is ideal for graduate students and researchers in wireless communications, as well as for wireless and telecom engineers.
(source: Nielsen Book Data)

• IntroductionFundamentals of Machine Learning and SoftcomputingMultilayer PerceptronsHopfield Networks and Boltzmann MachinesCompetitive Learning and ClusteringRadial Basis Function NetworksPrincipal Component Analysis NetworksFuzzy Logic and Neuro-fuzzy SystemsEvolutionary Algorithms and Evolving Neural NetworksDiscussion and OutlookAppendix: Mathematical Preliminaries.
• (source: Nielsen Book Data)

Conventional model-based data processing methods are computationally expensive and require experts' knowledge for the modelling of a system; neural networks provide a model-free, adaptive, parallel-processing solution. "Neural Networks in a Softcomputing Framework" presents a thorough review of the most popular neural-network methods and their associated techniques. This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model. "Neural Networks in a Softcomputing Framework" is an ideal textbook for graduate students and researchers in this field because in addition to grasping the fundamentals, they can discover the most recent advances in each of the popular models. The systematic survey of each neural-network model and the exhaustive list of references will enable researchers and students to find suitable topics for future research. The important algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence.
(source: Nielsen Book Data)

• Chapter 1. A DGS loaded Compact Super - Wideband Antenna for Microwave Imaging Application
• Chapter 2. A Study on Repeated Game Theory in Wireless Sensor Networks Security
• Chapter 3. An Overview of Information-Centric Network: Concepts, Network Architecture, Comparison, and Difficulties
• Chapter 4. Automated Mishap Detection and Prevention System for Vehicles
• Chapter 5. Autonomous Drone Using Time of Flight Sensor for Collision Avoidance
• Chapter 6. Collaborative Communication Models in Non-Cash Food Assistance (Bantuan Pangan Non-Tunai, Bpnt) Program: Towards Community Resilience
• Chapter 7. Communication technology for information exchange using short-range unmanned aerial vehicles
• Chapter 8. Evaluative Aspects of Wireless Sensor Networks Reliability Model: A Case Study
• Chapter 9. Implementation of 3D Object Models for Mobile Applications in UI/UX Design using SceneView API
• Chapter 10. Latest Trends in Wireless Network Optimization using Distributed Learning
• Chapter 11. Malware Classification in Local System Executable Files Using Deep learning
• Chapter 12. New generation 3D optical switch for free pace optical networks
• Chapter 13. Terrain Dimensions and Node Density Analysis of MANET using NS2 and BonnMotion
• Chapter 14. Towards Secure Fault-tolerant Wireless Sensor Communication: Challenges and Applications
• Chapter 15. Utilizing Data from Quick Access Recorder to Predict Faulty Processing on Aircrafts. etc.

The book is a collection of high-quality research papers presented at Intelligent Communication Technologies and Virtual Mobile Networks (ICICV 2023), held at Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India, during February 1617, 2023. The book shares knowledge and results in theory, methodology, and applications of communication technology and mobile networks. The book covers innovative and cutting-edge work of researchers, developers, and practitioners from academia and industry working in the area of computer networks, network protocols and wireless networks, data communication technologies, and network security.

• E-learning based Collaborative Learning Experience in the Education Paradigm.- Using Clean Architecture Principles to Improve the Design and Implementation of the Mobiles Online Platform.- Detection of Arrhythmia using Convolution Neural Networks.- The Hybrid Vision Transformer Approach for Hyperpigmentation Nail Disease Detection.- Covid19 Fake News Detection Using Glove and Bi-LSTM.- Combinatorial Test Perspective on Test Design of SDN Controllers.
• (source: Nielsen Book Data)

This book features high-quality research papers presented at the 2nd International Conference on Sustainable Expert Systems (ICSES 2021), held in Nepal during September 17-18, 2021. The book focusses on the research information related to artificial intelligence, sustainability, and expert systems applied in almost all the areas of industries, government sectors, and educational institutions worldwide. The main thrust of the book is to publish the conference papers that deal with the design, implementation, development, testing, and management of intelligent and sustainable expert systems and also to provide both theoretical and practical guidelines for the deployment of these systems.
(source: Nielsen Book Data)

• Ranking roughly tourist destinations using BERT based semantic search.- Discerning the Application of Virtual Laboratory in Curriculum Transaction of Software Engineering Lab Course from the Lens of Critical Pedagogy.- Drought Prediction using Recurrent Neural Networks and Long Short-Term Memory model.- A Deep Learning Framework for Classification of Hyperspectral Images.- Improved Security on Mobile Payments Using IMEI Verification.- Analytics and Data Computing for the Development of the Concept Digitalization in Business and Economic Structures.- Smart Door Locking System using IoT -A Security for Railway Engine Pilots.- Designing and Implementing a Distributed Database for Microservices Cloud-Based Online Travel Portal.- A comparative study of a new customized bert for sentiment analysis.- Twitter Sentiment Analysis Using Naive Bayes Based Machine Learning Technique.- Rainfall Forecasting System Using Machine Learning Technique and IoT Technology for a Localized Region.- Infrastructure as Code (IaC): Insights on Various Platforms.- Breast Cancer Prediction using different Machine Learning Algorithm.- A Proposed System for Understanding the Consumer Opinion of a Product Using Sentiment Analysis.- Comparative study of Machine Learning and Deep learning for Fungi classification.- Personality as a predictor of Computer Science Students' Learning Motivation.- Prediction and analysis of liver disease using extreme learning machine.- Deep-learning based quality assurance of silicon detectors in Compact Muon Solenoid experiment.- An Effectual Analytics and Approach for Avoidance of Malware in Android using Deep Neural Networks.- A One-Stop Service Provider for Farmers Using Machine Learning.- Fuzzy Logic Based Control of SEPIC Converter for Vehicle to Grid Application.- Social media mining to detect mental health disorders using Machine learning.- Using Deep Learning Models for Crop and Weed Classification at Early Stage.- FaceMask detection and social distancing using Machine Learning with Haarcascade algorithm.
• (source: Nielsen Book Data)

This book gathers selected papers presented at International Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), jointly organized by Tribhuvan University, Nepal and Prince of Songkla University, Thailand during 16 - 17 June, 2022. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes. .
(source: Nielsen Book Data)

• OTT (Netflix) Film Recommender System using Data Mining.- Dietary Assessment and Nutritional Analysis using Deep Learning.- Analyzing Game Theory Applications in a Layered Perspective for a Non-Cooperative Environment with the Existence of Nash Equilibria in Various fields of Research.- Essay Scoring Systems using AI and Feature Extraction: A Review.- Development of Real Time Violence Detection with Raspberry Pi.- Secure Optical Image Encryption and Data Hiding Technique in Compression Domain Using Dual Key Based Bit Swapping.
• (source: Nielsen Book Data)

This book includes high quality research papers presented at the International Conference on Communication, Computing and Electronics Systems 2021, held at the PPG Institute of Technology, Coimbatore, India, on 28-29 October 2021. The volume focuses mainly on the research trends in cloud computing, mobile computing, artificial intelligence and advanced electronics systems. The topics covered are automation, VLSI, embedded systems, optical communication, RF communication, microwave engineering, artificial intelligence, deep learning, pattern recognition, communication networks, Internet of Things, cyber-physical systems, and healthcare informatics.
(source: Nielsen Book Data)

• Analysis of Healthcare Industry Using Machine Learning Approach: A Case Study in Bengaluru Region.- Dynamic Document Localization for Ecient Mining.- SentiSeries: A Trilogy of Customer Reviews, Sentiment Analysis and Time Series.- Video Summarization using Fully Convolutional Residual Dense Network.- An Efficient Deep Learning Approach for Detecting Pneumonia Using the Convolutional Neural Network.- QMCDS: Quantum Memory for Cloud Data Storage.- A Study towards Bangla Fake News Detection using Machine Learning and Deep Learning.- A Deep Learning Approach to Analyze the Propagation of Pandemic in America.- Graph Convolution Based Joint Learning of Rumour with Content, User Credibility, Propagation Context and Cognitive as well as Emotion Signals.- Deep Learning based Real Time Object Classification and Recognition using Supervised Learning Approach.
• (source: Nielsen Book Data)

This book gathers selected papers presented at the International Conference on Sentimental Analysis and Deep Learning (ICSADL 2021), jointly organized by Tribhuvan University, Nepal; Prince of Songkla University, Thailand; and Ejesra during June, 18-19, 2021. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes. Meanwhile, deep learning emerges as the revolutionary paradigm with its extensive data-driven representation learning architectures. This book discusses all theoretical aspects of sentimental analysis, deep learning and related topics.
(source: Nielsen Book Data)

• Implementation of Machine and Deep Learning Algorithms for Intrusion Detection System.- Information Protection Means Using a Genetic Algorithm.- Classification of Breast Cancer Using CNN and Its Variant.- Systematic Approach for Network Security Using Ethical Hacking Technique.- Analysis of Modulation Techniques for Short Range V2V Communication.
• (source: Nielsen Book Data)

The book is a collection of high-quality research papers presented at Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), held at Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India, during February 10-11, 2022. The book shares knowledge and results in theory, methodology and applications of communication technology and mobile networks. The book covers innovative and cutting-edge work of researchers, developers and practitioners from academia and industry working in the area of computer networks, network protocols and wireless networks, data communication technologies and network security.
(source: Nielsen Book Data)

• Improved Grey wolf Optimization based Feature selection and classification using CNN for Diabetic Retinopathy detection.- Feature Selection Using Modified Sine Cosine Algorithm with COVID-19 Dataset.- Blood Cell Image Denoising based on Tunicate Rat Swarm Optimization with Median Filter.- A Hybrid Approach for Deep Noise Suppression using Deep Neural Networks.- Human Health Care Systems Analysis for Cloud Data Structure of Biometric System using ECG Analysis.- Data mining for Solving Medical Diagnostics Problems.- Classification of Diabetic Retinopathy using Ensemble of Machine Learning Classifiers with IDRID Dataset.- Epileptic Seizure Prediction Using Geometrical Features Extracted From HRV Signal.- An Extensive Survey on Outlier Prediction using Mining and Learning Approaches.- Performance Comparison of Data Security Strategies in Fog Computing.- Design and Simulation of a Direct-PSK Based Telecommand Receiver for Small Satellite
• Analysis of Data Aggregation and Clustering Protocol in Wireless Sensor Networks using Machine Learning.- DetecSec : A Framework to Detect and Mitigate ARP Cache Poisoning Attacks.- PAPR Reduction in SDR based OFDM System.
• (source: Nielsen Book Data)

This book mainly reflects the recent research works in evolutionary computation technologies and mobile sustainable networks with a specific focus on computational intelligence and communication technologies that widely ranges from theoretical foundations to practical applications in enhancing the sustainability of mobile networks. Today, network sustainability has become a significant research domain in both academia and industries present across the globe. Also, the network sustainability paradigm has generated a solution for existing optimization challenges in mobile communication networks. Recently, the research advances in evolutionary computing technologies including swarm intelligence algorithms and other evolutionary algorithm paradigms are considered as the widely accepted descriptors for mobile sustainable networks virtualization, optimization, and automation. To deal with the emerging impacts on mobile communication networks, this book discusses about the state-of-the research works on developing a sustainable design and their implementation in mobile networks. With the advent of evolutionary computation algorithms, this book contributes varied research chapters to develop a new perspective on mobile sustainable networks.
(source: Nielsen Book Data)

• Utilization of Sensors for Energy Generation using Pressure or Vibrations.- Modeling and Optimization of Discrete Evolutionary Systems of Information Security Management in a Random Environment.- Gender Identification using Ensemble Linear Discriminant Analysis Algorithm based on Facial Features.- Software Stack for Autonomous Vehicle: Motion Planning.- Transformers for Speaker Recognition.- Real-time Face Mask Detection using MobileNetV2 Classifier.- Spoken Language Identification for Native Indian Languages using Deep Learning Techniques.- Smart Attendance System using Machine Learning Algorithms.- Novel Approach to Phishing Detection Using ML and Visual Similarity.- Text Summarization of Articles using LSTM and Attention-based LSTM.
• (source: Nielsen Book Data)

This book involves a collection of selected papers presented at International Conference on Machine Learning and Autonomous Systems (ICMLAS 2021), held in Tamil Nadu, India, during 24-25 September 2021. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers selected papers in the area of emerging modern mobile robotic systems and intelligent information systems and autonomous systems in agriculture, health care, education, military and industries.
(source: Nielsen Book Data)

• Image analysis and method: Enhanced Acoustic Noise Reduction Techniques for Magnetic Resonance Imaging System
• Rough Rice Grading in the Philippines Using Infrared Thermography
• An Interpretable Hybrid Recommender Based on Graph Convolution to Address Serendipity
• Network Model and Function Analysis of Mobile Network: A Geometry-based Strategic Placement of RISs In millimeter Wave Device to Device Communication
• Obstacle Aware Link Selection for Stable Multicast D2D Communications
• Mobility Aware Path Selection for Millimeterwave 5G Networks in the Presence of Obstacles
• A Probabilistic Analysis of the Delay in RIS Assisted SISO D2D Communication using Chernoff's Bounds
• An Empirical Analysis on Lossless Compression Techniques: Enhancing IoT Security through Deep Learning-based Intrusion Detection
• A Security and Vulnerability Assessment on Android Gambling Applications
• A Compliance Based and Security Assessment of Bring Your Own Device (BYOD) in Organizations
• A Compliance Based and Security Assessment of Bring Your Own Device (BYOD) in Organizations
• AI -based system model and algorithm: Application of Machine Learning in Predicting Crime Links on Specialized Features
• An Empirical Analysis on Lossless Compression Techniques
• An Analysis of the Performance Changes of the Model by Reducing the Input Feature Dimension in Stock Price Forecasting
• A Hybrid Algorithm by Incorporating Neural Network and Metaheuristic Algorithms for Function Approximation and Demand Prediction Estimation
• Deep QA: An Open-Domain Dataset of Deep Questions and Comprehensive Answers
• Tropical Cyclone Analysis and Accumulated Precipitation Predictive Model Using Regression Machine Learning Algorithm
• Mapping Learning Algorithms on Data, A Promising Novel Methodology to Compare Learning Algorithms

This book constitutes refereed proceedings of the Third International Conference on Computer and Communication Engineering, CCCE 2023, held in Stockholm, Sweden, in March 2023. The 18 full papers presented were carefully reviewed and selected from 36 submissions. The papers are organized in the following topical sections: image analysis and method; network model and function analysis of mobile network; system security estimation and analysis of data network; and AI-based system model and algorithm

• Information Science and Mobile Communication.- Towards Intelligent Management of Internet of Modern Drones.- Ordering Algorithm as a Support for Children with ADHD through the Development of Bilingual and Interactive Videogames.- Detection of lateral road obstacles based on the Haar Cascade classification method in video surveillance.- Industrial IoT Solution for Powering Smart Manufacturing Production Lines.- Mobile Network Operators' cost efficient 5G deployment with Hyperscalers co-investment in Public Cloud.- Overview of Information System Testing Technology under the "Cloud + Microservices" Mode.- Image Denoising using A Deep Auto-encoder Approach based on Beetle Antennae Search Algorithm.- Diversity Technology Research in Wireless Communication Systems.- Study on Solving Algorithm of T Matrix Eigenvalues based on C Programming Language.- Computer and Electronic Engineering.- Federated Offline Reinforcement Learning for Autonomous Systems.- A New Smart Controller Model using Feedback and Feedforward for Three Phase Inverter.- Adaptive Design Space Reconstruction Method in Surrogate based Global Optimization.- Research on Vibration Phase Measurement Technology Based on Laser Interference Waveform Demodulation.- An Accurate Algorithm for Calibration-free Wavelength Modulation Spectroscopy Based on Even-order Harmonics.- A Hierarchical Multi-Objective Programming Approach to Planning Locations for Macro and Micro Fire Stations.- Utilization of Machine Learning Algorithm to Determine Factors Affecting Response to Action among Filipinos Toward the 2020 Taal Volcano.
• (source: Nielsen Book Data)

This book constitutes refereed proceedings of the 2nd International Conference on Computer and Communication Engineering, CCCE 2022, held in Rome, Italy, March 11-13, 2022. The 9 full papers and 8 short papers presented in this volume were carefully reviewed and selected from a total of 36 submissions. The papers in the volume are organised according to the following topical headings: information science and mobile communication; computer and electronic engineering.
(source: Nielsen Book Data)

• A Survey of Machine Learning Techniques Applied for Automatic Traffic Light Recognition.- Machine Learning based Detection and Classification of Heart Abnormalities.- An Evaluation of Multiclass Leaf Classification using Transfer Learning Techniques.- Scene Generated with Text guidance(VAAB System).- Machine Learning Approaches for Image Quality Improvement.- Natural Disaster Prediction by using Image based Deep Learning and Machine Learning.- A Novel Multi-Objective Differential Evolution Algorithm for Clustering Data Streams.- An Algorithm for Pre-processing of Areca nut for Quality Classification.- An Effect of Binarization on Handwritten Digits Recognition by Hierarchical Neural Networks.- Deep Convolutional Neural Networks (CNNs) to Detect Abnormality in Musculoskeletal Radiographs.
• (source: Nielsen Book Data)

This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications. The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking.
(source: Nielsen Book Data)