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Book
Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
Authors: --- ---
Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.

Keywords

Research & information: general --- Mathematics & science --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- n/a


Book
Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
Authors: --- ---
Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

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Export citation

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Bookmark

Abstract

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.


Book
Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
Authors: --- ---
Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.

Keywords

Research & information: general --- Mathematics & science --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle


Book
Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)
Authors: ---
ISBN: 3039213768 303921375X Year: 2019 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR

Keywords

n/a --- FPGA --- recurrence plot (RP) --- residual learning --- neural networks --- driver monitoring --- navigation --- depthwise separable convolution --- optimization --- dynamic path-planning algorithms --- object tracking --- sub-region --- cooperative systems --- convolutional neural networks --- DSRC --- VANET --- joystick --- road scene --- convolutional neural network (CNN) --- multi-sensor --- p-norm --- occlusion --- crash injury severity prediction --- deep leaning --- squeeze-and-excitation --- electric vehicles --- perception in challenging conditions --- T-S fuzzy neural network --- total vehicle mass of the front vehicle --- electrocardiogram (ECG) --- communications --- generative adversarial nets --- camera --- adaptive classifier updating --- Vehicle-to-X communications --- convolutional neural network --- predictive --- Geobroadcast --- infinity norm --- urban object detector --- machine learning --- automated-manual transition --- red light-running behaviors --- photoplethysmogram (PPG) --- panoramic image dataset --- parallel architectures --- visual tracking --- autopilot --- ADAS --- kinematic control --- GPU --- road lane detection --- obstacle detection and classification --- Gabor convolution kernel --- autonomous vehicle --- Intelligent Transport Systems --- driving decision-making model --- Gaussian kernel --- autonomous vehicles --- enhanced learning --- ethical and legal factors --- kernel based MIL algorithm --- image inpainting --- fusion --- terrestrial vehicle --- driverless --- drowsiness detection --- map generation --- object detection --- interface --- machine vision --- driving assistance --- blind spot detection --- deep learning --- relative speed --- autonomous driving assistance system --- discriminative correlation filter bank --- recurrent neural network --- emergency decisions --- LiDAR --- real-time object detection --- vehicle dynamics --- path planning --- actuation systems --- maneuver algorithm --- autonomous driving --- smart band --- the emergency situations --- two-wheeled --- support vector machine model --- global region --- biological vision --- automated driving

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