: Proposes a method using YOLO and ResNet-50 to detect and classify vehicles into four size categories and eight color categories with high accuracy.
Several research papers focus on the classification and recognition of using various computational methods, primarily for intelligent traffic management and autonomous driving. Key research papers and their focus areas include: Deep Learning and Computer Vision : vehicle*type
: Introduces a classification scheme for surveillance images using deep learning and data augmentation to handle varying camera resolutions. Feature-Based Approaches : : Proposes a method using YOLO and ResNet-50
: Discusses a model specialized in recognizing cars, SUVs, and vans by combining multi-layer features to improve precision in complex traffic scenarios. Feature-Based Approaches : : Discusses a model specialized
: Uses Principal Components Analysis (PCA) to extract features from vehicle fronts for classification, specifically handling day and night conditions separately. Comprehensive Reviews :