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Artificial Intelligence and Machine Learning and Its Application in the Field of Computational Visual Analysis

Digvijay PandeyDepartment of Technical Education, Government of Uttar Pradesh,, IndiaVinay Kumar NassaBinay Kumar PandeyDepartment of Information Technology, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, IndiaBlessy ThankachanSchool of Computer Applications, JECRC University, IndiaPankaj DadheechSwami Keshvanand Institute of Technology, Management, and Gramothan, IndiaDarshan A. MahajanNICMAR University, IndiaA. Shaji George
2024en
ABI

Аннотация

Artificial intelligence and machine learning applications in image processing are examined in this chapter. It covers AI methods including supervised, unsupervised, reinforcement, and deep learning. Genetic algorithms, rule-based systems, expert systems, and fuzzy logic are AI methods. SVM, decision trees, random forests, K-means clustering, and PCA are machine learning methods. CNN, RNN, and GANs are utilised for object recognition, classification, and segmentation. The chapter discusses how artificial intelligence and machine learning affect accuracy, efficiency, and decision-making. The need to choose proper measurements and procedures for assessment and performance analysis is also stressed. Ethics like justice, privacy, transparency, and human-AI cooperation are covered in the chapter.

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