• M. Anusha Rani
• Cheepurupalli Ekshitha
• Pavuluri Sri Lakshmi
• Masanam Sri Poojitha
• Lanka Rohini

Advances in object recognition technology have opened new avenues for improving the safety, efficiency, and automation of railway systems. Powered by deep learning and computer vision algorithms. Object recognition plays an important role in various aspects of railway operations. significantly Including real-time tracking collision avoidance Avoiding obstacles on the tracks This paper studies the application of object detection in railway systems. Accident prevention and performance tracking, performance training optimization, and focus on role improvement. It uses object detection through camera sensors placed at key locations in the rail system such as intersections, platforms, tracks, etc. These systems can identify and classify objects on the tracks including animals, vehicles or humans and alert operators or activate incidents. automatic emergency Braking neural networks Convolutional (CNN) and leverages technologies such as machine learning models. For modern object detection systems to achieve high accuracy in real-time detection of dangerous situations.

Deep Learning, Convolutional Neural Networks, Accuracy, Clustering, Detection.

"RAILWAY SYSTEM BASED ON OBJECT DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.364-372, November-2024, Available :http://www.jetir.org/papers/JETIRGO06037.pdf

"RAILWAY SYSTEM BASED ON OBJECT DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp364-372, November-2024, Available at : http://www.jetir.org/papers/JETIRGO06037.pdf