Multilevel Random Forest Algorithm in Image Recognition for Various Scientific Applications

Abstract

Artificial Intelligence (AI) is a field of research where researchers and scientists are trying to understand our nature and incorporate that understanding in the machine and computer to serve our society. Machine learning (ML) is another aspect of AI. Several algorithms are inverted, modified and updated to characterize the understanding of the nature and implement intelligence artificially within the machine. One major challenge of AI is to understand the object. The first identification of an object is visual information. There are several mechanisms and algorithms to identify an object. Every algorithm has some pros and cons. Among these algorithms, decision tree and random forest algorithm, which is a combination of decision tree algorithms, can play a very effective role. This work shows the application of the multilevel random forest algorithm (MRFA) which is a modified application of the random forest algorithm is introduced for image classification.