An Exploration on Explainable AI with Background and Motivation for XAI

This article deals with the exploration of XAI in the field of Image processing and Machine Learning. Machine learning models are rapidly used to make important decisions in applications such as medical diagnosis, Law, Business, and many more. It needs to know how the outcomes and predictions are being made in machine learning models by considering the input datasets. This paper would like to explore the black box of machine learning models and review the current challenges and opportunities to explain the predictions and outcomes made by the ML model through the concept of XAI. XAI is explainable AI it is also known as Interpreting ML Model, Explainable models. This paper does a literature review of latest findings and surveys published in various reputed Journals.