Affiliation:
1. Muthayammal Engineering College, India
2. Georgia State University, USA
Abstract
This chapter explores the role of AI and machine learning (ML) in image processing, focusing on their applications. It covers AI techniques like supervised learning, unsupervised learning, reinforcement learning, and deep learning. AI techniques include rule-based systems, expert systems, fuzzy logic, and genetic algorithms. Machine learning techniques include SVM, decision trees, random forests, K-means clustering, and PCA. Deep learning techniques like CNN, RNN, and GANs are used in tasks like object recognition, classification, and segmentation. The chapter emphasizes the impact of AI and ML on accuracy, efficiency, and decision-making. It also discusses evaluation metrics and performance analysis, emphasizing the importance of selecting appropriate metrics and techniques. The chapter also addresses ethical considerations, such as fairness, privacy, transparency, and human-AI collaboration.
Cited by
56 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Transforming Hospitality, Personalized Medicine, and Adaptive Learning;Advances in Medical Technologies and Clinical Practice;2024-09-27
2. Performance Improvements of Electric Vehicles Using Edge Computing and Machine Learning Technologies;Advances in Mechatronics and Mechanical Engineering;2024-07-26
3. Edge Computing and Machine Learning Integration for Autonomous Electrical Vehicles;Advances in Mechatronics and Mechanical Engineering;2024-07-26
4. MNSIT Handwritten Digit Recognition using CNN;2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN);2024-07-03
5. Leveraging Drone and GPS Technologies For Precision Agriculture;Advances in Environmental Engineering and Green Technologies;2024-06-28