123853 Apr 2026

: 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 :

: It is frequently used as a digital identifier within the Inderscience Publishers system for various engineering and technology manuscripts.

While primarily an academic identifier for the vehicle classification study, the number also appears in other specialized contexts: 123853

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

: It serves as a course section ID for INTS 435-D01: Leadership in a Changing Environment at George Mason University for the Summer 2026 session, taught by Marintha Miles. : The study aims to replace traditional, manual,

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

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

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