Automated License number recognition in python
In today's Era, the IT sector is moving more and more towards automation. Now every company is trying to provide its users with the facility to perform their task without the need for any human intervention. In this talk, we are addressing a similar problem of automating the vehicle parking systems.
Automated license plate recognition(ALPR) is a well-known problem where we try to extract the license number from a cars number plate using machine learning algorithms. The scope of its real-world application ranges from highway toll plaza to automated parking and charging of future electric cars. This problem has been targeted with a variety of algorithms like traditional template matching to advance deep learning algorithms like YOLO.
Here we will be presenting a combination of little template matching clubbed with some deep learning to solve this problem in the most simplistic way.
The session is fully for beginner's who have just entered the field of machine learning and deep learning. Every small detail will be covered in the talk. Beginner's knowledge of the following items would be helpful.
- Knowledge of Numpy: A good resource for the same is : Udemy Deep learning Stack
- Basic understanding of OpenCV: A good resource for the same is:Udemy OpenCV Basics. This much is enough, we would also be covering the important content in the talk.
- Basic Knowledge of Convolutional Neural Networks: An excellent resource to understand this is CNN by Datacamp. The motive should be to understand the basic working of Convolutional Neural Networks. The coding part will be explained in the talk as well relating each step to it's working.
- Knowledge of basic metrics: These are ways to evaluate the performance of our model. An excellent resource is:Metrics for Evaluations
The GitHub repository and the talk slide are:
- Slides: Will be updated soon.
- Github repo: Will be updated soon.
The talk will be presented by 3 speakers who are presently 4th-year students from Jaypee Institute of information technology, Noida. They are machine learning enthusiasts and researchers. They had been working in this field for the past one-half year and have worked on a variety of projects ranging from customer segmentation, recommendations to the projects from the field of computer vision, deep learning and reinforcement learning. They have also worked with an AI startup where they had to predict customer churn.