Abstract
Recognizing patterns and identifying different objects by a machine using human intelligence is a challenging issue in real world. Machine learning techniques can help a machine to achieve automating manual tasks and advanced technologies such as self-driving car and robot in industry. The automated analysis of medical images, tax returns to audit, automatic inspection of printed circuits, etc. are some more applications of pattern recognition for which we are required to design a machine which classifies perfectly. This paper presents different machine learning-based pattern recognition approaches to recognize an object. The first step in building an automatic classification is separating the objects from its background. Based on the literature survey, this paper encompasses the various models of pattern recognition for image analysis and recognition with the aid of machine learning algorithms.
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Madhuri, G.R., Jagadale, B.N., Salma, N., Akshata, G.M., Gupta, A., Chandrakantha, T.S. (2024). Machine Learning-Based Pattern Recognition Models for Image Recognition and Classification. In: Guru, D.S., Kumar, N.V., Javed, M. (eds) Data Analytics and Learning. ICDAL 2022. Lecture Notes in Networks and Systems, vol 779. Springer, Singapore. https://doi.org/10.1007/978-981-99-6346-1_8
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DOI: https://doi.org/10.1007/978-981-99-6346-1_8
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