Machine Learning in Sensing and Imaging Systems

Abstract

As technology is progressing, Machine Learning (ML) is playing bigger role in science and technology. As, devices, gadgets, machines are becoming smarter, number of sensors present in them is ever growing with more and more data is collected. To make these devices smarter, this data can be used for taking decisions and improving the quality of output obtained. In the present work ML has been used for two specific problems. One where it is required to classify various gases detected by an array of sensors, and in second problem ML has been used to improve the image quality of data obtained from imaging systems. For classification problem, array of Quartz Tuning Fork (QTF) sensors have been used to detect various Volatile Organic Compounds (VOCs). Different classification algorithms have been tried and tested and their applicability to this problem has been analyzed. newline