Sensors Data Processing Using Machine Learning.

This document discusses the use of machine learning and deep learning in data processing for various sensors. It includes research papers on topics such as toxicity detection in online discussions, evaluation of infrastructure for connected and automated vehicles, an IoT-based system for managing classroom activities during COVID-19, text classification in different languages, multi-delay identification methods, attention heat maps in benchmarks, video quality assessment with packet loss, optimization of 3DCNN models for human activity recognition, an IoT-based connected university system, usability evaluation of Apple MacBook Pro laptops for machine learning research, data augmentation for student behavior identification, defect image classification in ductile cast iron pipe images, supervised classification models for image classification, and sample selection methods for training classification models. The authors provide detailed explanations of each research topic and present their findings and conclusions. [Extracted from the article]