Identification of research trends associated with image capture using machine learning

Abstract

Image recognition and capture has evolved over the years. From capturing a moment through analog black and white cameras, to detecting objects and motion through the implementation of sensors in different contexts. Currently, image capture devices use different machine learning techniques for motion detection or object recognition in different sectors such as mobility, agriculture, climate, security, among others. Given the diversity of applications of image capture, this research aims to analyze research trends in the application of machine learning in image capture devices in order to guide the planning of future studies. This is done through bibliometrics using the PRISMA2020 decision. As a main result, it was found that since 2020 interest in research on this topic has been increasing. In addition, it is concluded that computer vision and object detection are emerging research topics in which future lines of research can be framed.