• Nikhil Sanjay Thakur
• Monika. S. Sherkhane
• Mayur . S. Thigale
• Mrs. Rekha Kakade

Computer vision is a rapidly evolving field that enables computers to interpret and understand the visual world by processing digital images or video. This research project aims to explore advanced techniques in computer vision, focusing on object detection, recognition, and image segmentation. Leveraging deep learning architectures, particularly convolutional neural networks (CNNs), this study investigates the accuracy and efficiency of various algorithms in real-time image analysis. Additionally, the integration of computer vision in autonomous systems, healthcare, and security will be examined to understand its potential applications and societal impact. The outcomes of this research are expected to contribute to improving current methods in visual data processing, offering more robust and scalable solutions for practical deployment in dynamic environments. Key areas of exploration include the development of novel architectures for improving accuracy in complex scenes, reduction of computational costs, and addressing challenges in occlusion and low-light conditions. This paper also evaluates the ethical considerations and biases inherent in computer vision systems, ensuring that future advancements prioritize fairness and inclusivity.

Computer Vision, Image Processing, Machine Learning, Robotics

"Advancements in Computer Vision Techniques and Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 2, page no.a121-a124, February-2025, Available :http://www.jetir.org/papers/JETIR2502017.pdf

"Advancements in Computer Vision Techniques and Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 2, page no. ppa121-a124, February-2025, Available at : http://www.jetir.org/papers/JETIR2502017.pdf