Traffic Sign Classification using Deep Learning | Python Machine Learning Final Year IEEE Project

Traffic Sign Classification using Deep Learning | Python Final Year IEEE Project. 🛒Buy Link: https://bit.ly/3R02xLd (or) To buy this project in ONLINE, Contact: 🔗Email: [email protected], 🌐Website: https://www.jpinfotech.org 🔬Our Proposed Project Title: Real-Time Traffic Sign Recognition and Classification with Deep Learning. 💡Implementation Code: Python. 🔬Algorithm / Model Used: MobileNet Architecture & YOLOv5. 🌐Web Framework: Flask. 🖥️Frontend: HTML, CSS, JavaScript. 💰Cost (In Indian Rupees): Rs.5000/. 📘Project Abstract: 👉The project "Traffic Sign Classification using Deep Learning" represents a significant advancement in the field of computer vision, specifically focusing on the recognition and classification of traffic signs. Leveraging the power of Python, two distinctive models were employed to address the complex challenges associated with traffic sign classification: MobileNet Architecture and YOLOv5. 👉With MobileNet Architecture, an impressive level of performance was achieved, with a Training Accuracy of 97.00% and Validation Accuracy of 98.00%. This achievement was realized through the utilization of a meticulously curated dataset comprising 4,170 images encompassing a diverse array of 58 traffic sign classes, including but not limited to speed limits, directional instructions, prohibitory signs, and hazard warnings. These classes span the entire spectrum of traffic regulation, ensuring comprehensive coverage of the subject matter. 👉Moving forward, the implementation of YOLOv5 introduced real-time traffic sign recognition using image data and real time web camera data. This model was trained on a dataset comprising 39 unique traffic sign classes. These classes encompass a wide range of signs, such as pedestrian crossings, speed limits, warnings, and regulatory signs, contributing to the project's practical applicability in real-world scenarios. 📌Project Title: Traffic Sign Classification using Deep Learning. 📌REFERENCE: Ramya Sree Pothineni, Srinivas Inampudi, Lakshmi Yesaswini Gudavalli, T. Lakshmi Surekha, “Traffic Sign Classification using Deep Learning”, 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), IEEE CONFERENCE, 2023. 🏷️tags: #python #pythonprojects #machinelearningproject #pythonprogramming #pythonprojectforbeginners #pythonprojectideas #pythonmachinelearning #machinelearning #machinelearningpython #finalyearproject #ieeeprojects #finalyearprojects #datascience #datascienceproject #artificialintelligenceproject #projects #deeplearning #deeplearningproject #computerscienceproject #deeplearningprojects #majorprojects #academicprojects #majorproject