The book presents a remarkable collection of chapters covering a wide range of topics in the areas of intelligent systems and artificial intelligence, and their real-world applications. It gathers the proceedings of the Intelligent Systems Conference 2019, which attracted a total of 546 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process, after which 190 were selected for inclusion in these proceedings.
As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle a host of problems more effectively. This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for an international conference as a venue for reporting on the latest innovations and trends.
Thisbook collects both theory and application based chapters on virtually all aspects of artificial intelligence; presenting state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision for future research, it represents a unique and valuable asset.
表中的内容
A New Approach of Service Platform for Water Optimization in Lettuce Crops using Wireless Sensor Network.- A Novel AI based Optimization of Node Selection and Information Fusion in Cooperative Wireless Networks.- Using Automated State Space Planning for Effective Management of Visual Information and Learner’s Attention in Virtual Reality.- Pedestrian Recognition and Obstacle Avoidance for Autonomous Vehicles using Raspberry Pi.- Analysing Data Set of the Bike-sharing System Demand with R Scripts: Mexico City Case.- Less-than-truckload Shipper Collaboration in the Physical Internet.- Automatic Curation System using Multimodal Analysis Approach (MAA).- Figurative Language Grounding in Humanoid Robots.- LIT: Rule based Italian Lemmatizer.- Combining Diffusion Processes for Semi-Supervised Learning on Graph Structured Data.- A Review of Continuous Blood Glucose Monitoring and Prediction of Blood Glucose Level for Diabetes Type 1 Patient in Different Prediction Horizons (PH) using Artificial Neural Network (ANN).- Ensemble Approach for Left Ventricle Segmentation.- Autonomous Robot Navigation with Signaling based on Objects Detection Techniques and Deep Learning Networks.- GMC: Grid Based Motion Clustering in Dynamic Environment.- A Machine Learning Approach for Classification of Tremor- a Neurological Movement Disorder.
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