A New CNN-Based Approach to Multi-Directional Car License Plate Detection PROJECT TITLE : A New CNN-Based Method for Multi-Directional Car License Plate Detection ABSTRACT: This study presents a novel convolutional neural network (CNN)-based method for high-accuracy real-time car licence plate detection. Many modern methods of detecting a car's licence plate are only good under very specific conditions or under very strong assumptions. However, they perform poorly if the assessed car licence plate images have a degree of rotation due to the manual capture by traffic police or deviation of the camera. In order to detect car licence plates in both directions, we propose a CNN-based MD-YOLO framework. Our method, which makes use of precise rotation angle prediction and a fast intersection-over-union evaluation strategy, effectively manages rotational issues in real-time scenarios. Several experiments have been conducted to show that the proposed method outperforms other current state-of-the-art methods in terms of better accuracy and lower computational cost. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Feature Extraction Object Detection Image Recognition Machine Learning Projects Python Artificial Intelligence Projects Python Deep Learning Projects License Plate Detection Convolutional Neural Network Python Image Processing Projects A New Approach to Moving Target Screening for SAR GMTI in the UHF Band Disease Prediction Using a Linear Model Based on Principal Component Analysis
