Pattern Recognition Using Computer Vision

This project, “Pattern Recognition using Computer Vision” focuses on developing a system capable of identifying and interpreting patterns in visual data through the use of machine learning algorithms. The goal is to address the limitations of traditional pattern recognition systems, such as low accuracy and inefficiency, by leveraging Logistic Regression. The proposed system will be evaluated on various datasets, with potential applications in fields such as healthcare, security, and autonomous vehicles. Pattern recognition is a fundamental aspect of computer vision, enabling machines to interpret and understand visual data by identifying patterns, objects, or features within images. With the advent of deep learning the field has seen significant advancements, leading to more accurate and efficient systems. This project focuses on leveraging these advancements to develop a comprehensive pattern recognition system that can be applied in various real-world scenarios, including image classification, object detection.