Retrospective Look at Machine Learning Techniques for Consistent Pattern Recognition

Author(s)

Sucheta Bhowmick , Atif Ali Khan , Zameer Ahmad ,

Download Full PDF Pages: 40-47 | Views: 377 | Downloads: 121 | DOI: 10.5281/zenodo.5592749

Volume 10 - September 2021 (09)

Abstract

The main goal of example recognition is controlled or unassisted arranging. Of the various structures where pattern recognition is often discussed, this section examines and utilizes 50 relevant evaluations between 2014 and 2020. Recently, brain organizing strategies and approaches derived from quantifiable learning hypothesis have gotten greater attention. Design portrayal, highlight extraction and determination, bunch investigation, classifier plan and learning are some of the difficulties that should be considered while designing an acknowledgement framework. To summarize and examine some of the prominent approaches used in various phases of an example acknowledgement framework, and to identify cutting-edge research subjects and applications in this fascinating and challenging field. Various AI methods have brought pattern recognition systems quicker.

Keywords

Machine learning; neural network; pattern recognition; security; accuracy; classification  

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