Advances in Deep Learning, Artificial Intelligence and Robotics Proceedings of the 2nd International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2020

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.