My master thesis on Traffic Sign Recognition Using Computer Vision
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Updated
Jun 17, 2022 - Jupyter Notebook
My master thesis on Traffic Sign Recognition Using Computer Vision
Multi-class, single-image classification using MobileNet-CNN
This was the final project for the computer vision course.
this is my big project at the end of my Machine Learning courses
Train YOLO object detection model to find traffic signs in the images. Use OCR pipeline to extract the information from the signs with text.
Detection of traffic signs using videos or images can be performed from this program. I have used kaggle dataset for traffic signs detection and developed the YoloV4 model which will detect 4 types of traffic signs named speed limit, yield, mandatory, and other.
Traffic Sign Recognition Project for my Internship on Prime Layer
Contribution for Traffic Sign Detection and Warning System in real time with Custom Dataset & YOLOv8.
Detect and Classify Red Traffic Signs (Intredit/Prohibition Traffic Signs)
Coursework created for the COM3025 Deep Learning And Advanced AI module during my Computer Science BSc at Surrey University
Repository for the Traffic Sign Detection Project. Started on August 2020 by Kevin Um, this project seeks to detect and classify public traffic signs in real-time.
Extract signboards from environmental images using OpenCV
Custom object detection model for low clearance signs
RoadVisor is an augmented reality navigation application aimed at enhancing the driving experience. It combines real-time traffic information and advanced computer vision techniques to improve safety and efficiency on the road. The project is brought to life by a passionate team of computer engineering students.
Notebook and model for German Traffic Sign Recognition Benchmark (GTSRB) Dataset. The notebook contains an extensive EDA for the dataset and trains a CNN classifier on the benchmark.
Team project about traffic sign localization and classification for APS360 Applied Fundamentals of Machine Learning at the University of Toronto.
Realtime traffic sign detection on mobile
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