: Introduces a classification scheme for surveillance images using deep learning and data augmentation to handle varying camera resolutions. Feature-Based Approaches :
: Provides a historical account and technical review of how vehicle detection and classification have evolved from basic computer vision to modern high-accuracy neural networks. AI responses may include mistakes. Learn more vehicle*type
: Uses Principal Components Analysis (PCA) to extract features from vehicle fronts for classification, specifically handling day and night conditions separately. Comprehensive Reviews : : Introduces a classification scheme for surveillance images
: Proposes a method using YOLO and ResNet-50 to detect and classify vehicles into four size categories and eight color categories with high accuracy. vehicle*type
: Explores both geometric and appearance-based approaches for multi-class and intra-class vehicle classification.