Training an accurate AI model to identify license plate numbers requires using the right type of data. Should you use alpha-numeric text entries or actual images of license plates? Get the answer here.
Table of Contents
Question
What data will you use for training a model to identify numbers on vehicle license plates?
A. Multiple alpha-numeric entries of vehicle license plate values
B. Multiple images of different vehicle license plates
Answer
B. Multiple images of different vehicle license plates
Explanation
To train a machine learning model to accurately identify and extract the numbers on vehicle license plates, the best data to use is B) multiple images of different vehicle license plates.
Using actual images of license plates allows the model to learn the visual patterns and characteristics of real license plates. It can learn to identify the rectangular shape of the plates, the fonts and formats of the numbers and letters, and how to distinguish the license plate from the surrounding vehicle and environment.
In contrast, using text entries of license plate numbers (choice A) would not give the model the necessary visual information. It may learn the possible formats and character sequences of license plate numbers, but it wouldn’t know how to actually find and read the plates in an image.
Therefore, a dataset containing many diverse images of vehicles and license plates, with the license plate numbers labeled, is the ideal training data for this computer vision task. The images should cover different plate styles, vehicle types, lighting conditions, angles, etc. to create a robust model.
Google AI for Anyone certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Google AI for Anyone exam and earn Google AI for Anyone certification.