: The study aims to replace traditional, manual, or less efficient machine vision methods with a robust deep learning framework to identify vehicle types (e.g., sedan, SUV, truck) from image data. Methodological Workflow :

: The approach often combines CNNs for feature learning with Support Vector Machines (SVMs) to handle the final categorization, maximizing both accuracy and computational efficiency.

This research addresses a fundamental challenge in : the accurate and automated categorization of vehicles by their body types using advanced computer vision.

: Initial processing of raw images to ensure consistency and quality for the neural network.

: Utilizing Convolutional Neural Networks (CNNs) to automatically learn and extract complex visual patterns that distinguish different vehicle shapes.