Advances in Deep Learning, Artificial Intelligence and Robotics

This book of Advances in Deep Learning, Artificial Intelligence and Robotics (proceedings of ICDLAIR 2020) is intended to be used as a reference by students and researchers who collect scientific and technical contributions with respect to models, tools, technologies and applications in the field of modern artificial intelligence and robotics. Deep Learning, AI and robotics represent key ingredients for the 4th Industrial Revolution. Their extensive application is dramatically changing products and services, with a large impact on labour, economy and society at all. The research and reports of new technologies and applications in DL, AI and robotics like biometric recognition systems, medical diagnosis, industries, telecommunications, AI petri nets model-based diagnosis, gaming, stock trading, intelligent aerospace systems, robot control and web intelligence aim to bridge the gap between these non-coherent disciplines of knowledge and fosters unified development in next-generation computational models for machine intelligence.

Presents new technologies and applications in deep learning, artificial intelligence, and robotics Includes the results from the 2nd ICDLAIR held in Salerno, Italy Intends to be used as a reference by students and researchers

Inhalt

Deep Learning Based Classification System For Recognizing Local Spinach.- Fusion of Deep Learning Features for Wild Animal Detection.- Forecast Extreme CPU Usages under Peak Load using envelop EM Semi-Supervised Learning.- Classifying Case Facts and Predicting Legal Decisions of The Indian Central Information Commission: A Natural Language Processing approach.- On the implementation of a semantic model for intelligent vehicle navigation.- Twenty Years Of Assessment Of Drought Conditions Over The Gangapur Region Of Aurangabad District In Maharashtra (India)Using Remote Sensing Indices.- Educational Resources Recommender System for Teachers: Why and How?.- Hybrid Cloud Native Framework for Smart City Applications.- A Two-Stage Intrusion Detection System (TIDS) for Internet of Things.- Breast Cancer Detection Using Deep Convolutionnal Neural Networks And Raspberry Pi 3 Board.- An Improved Approach for Removal of Salt & Pepper Noise in MR Images.- Dual-Pathway Deep CNN for OfflineWriter Identification.- Real-time Urban Traffic Control of a complex junction.- A Multi-Agent System for Industrial Simulators Design.- Comparison of Current Convolutional Neural Network Architectures for Classification of Damaged and Undamaged Cars.- Intelligent agents for Multi-user Preference Elicitation.- Automatic Grading of Knee Osteoarthritis on the Kellgren-Lawrence Scale from Radiographs Using Convolutional Neural Networks.- Robust Model for Rural Education using Deep Learning and Robotics.- Action Recognition for Anomaly Detection using Transfer Learning and Deep Architectures.- Personalised federated learning with BERT fine tuning. Case study on Twitter sentiment analysis.- Use of Artificial Intelligence in Human Resource Management: Application of Machine Learning Algorithms to an intelligent Recruitment system.- Combining Active Semi-supervised Learning and Rare Category Detection.