CPSC 7560 - Computer Vision Applications in Urban Mobility

(3) Credit Hours

This 7000-level course focuses on computer vision (CV) techniques and deep learning applications pertinent to urban mobility. Building on fundamental machine learning concepts, the course covers essential topics in image processing, convolutional neural networks (CNNs), object detection, and segmentation, tailored to traffic flow analysis, vehicle detection, pedestrian safety, and other key mobility challenges. Students will learn how to design, train, and deploy CV models on Google Colab or HPC cluster, handling real-world transportation datasets. Through targeted assignments, a midterm examination, and a semester-long research project, students will gain both theoretical grounding and hands-on experience in implementing computer vision solutions for next-generation transportation systems. Prerequisites: CPSC 5440 or Department Head approval. Differential course fee will be assessed.

Effective Spring 2026.