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This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research, Computational Intelligence and Machine Intelligence including an introduction to the recent research and models.

Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

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Advances in Modern Artificial Intelligence.- Computing efficiently spectral-spatial classification of hyperspectral images on commodity GPUs.-Early Smoke Detection in Outdoor Space by Spatio-temporal Clustering using a Single Video Camera.-Using evolved artificial neural networks for providing an emergent segmentation with an active net model.-Obtaining Shape from SEM Image Using Intensity Modification via Neural Network.-Fuzzy Evidence Reasoning and Position Fixing Segmentation of Hyperspectral Images by Chromatic by t-Watershed.-Impact of Migration Topologies on Performance of Teams of A-Teams.-A Cooperative Agent-Based Multiple Neighborhood Search for the Capacitated Vehicle Routing Problem.-Building an Automatic Body Condition Scoring System using Active Shape Models and Machine Learning.- The Impact of Network Characteristics on the Accuracy of Spatial Web Performance Forecasts Using Multi-Agent Systems Technique for Developing an Autonomous Model used to Analyze Work-Stress Data.

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