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Artificial Intelligence and Machine Learning and Its Application in the Field of Computational Visual Analysis
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Author(s): Digvijay Pandey (Department of Technical Education, Government of Uttar Pradesh,, India), Vinay Kumar Nassa (Department of Information Communication Technology, Tecnia Institute of Advanced Studies, India), Binay Kumar Pandey (Department of Information Technology, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India), Blessy Thankachan (School of Computer Applications, JECRC University, India), Pankaj Dadheech (Swami Keshvanand Institute of Technology, Management, and Gramothan, India), Darshan A. Mahajan (NICMAR University, India)and A. Shaji George (Business System Department, Almarai Company, TSM, Riyadh, Saudi Arabia)
Copyright: 2024
Pages: 22
Source title:
Emerging Engineering Technologies and Industrial Applications
Source Author(s)/Editor(s): Younes El Kacimi (Ibn Tofail University, Morocco)and Khaoula Alaoui (Ibn Tofail University, Morocco)
DOI: 10.4018/979-8-3693-1335-0.ch003
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Abstract
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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