This Special Issue aims to seek high-quality papers from academics and industry-related researchers who conduct research on the development of machine learning models for IoT systems through machine learning, deep learning, big data, and IoT. The papers should focus on the development of efficient machine learning models to improve their running and training speeds, without sacrificing accuracy or increasing hardware costs. Topics of interest include, but are not limited to, Expert Systems, Fuzzy Logic, Computer Vision, Decision Trees, Genetic Algorithms, Swarm Intelligence, Cognitive Computing, Sentiment Analysis, Chatbots, Voice Recognition, Recommendation Systems, Predictive Analytics, Data Mining, Big Data, Internet of Things (IoT), Smart Cities, Smart Homes, Autonomous Vehicles, Augmented Reality, Virtual Reality, Image Recognition, Emotion Recognition, Personalization, Fraud Detection, Content Generation, Video Analytics, Medical Diagnosis, Energy Management, Supply Chain Management, Human-Robot Interaction, Speech Synthesis, Cybersecurity, Blockchain, Quantum Computing, Edge Computing, Cloud Computing, Reinforcement Learning, Knowledge Representation, Evolutionary Computing, Machine Perception, Explainable AI, Ethical AI, AI Policy and Regulation, Machine Learning, Deep Learning, Natural Language Processing, Robotics, and Automation.
Related Posts
