Computer Vision Basics

This course equips you with the foundational knowledge of Computer Vision (CV), a transformative technology with vast applications in Supply Chain Management (SCM). You'll explore how CV empowers machines to "see" and understand visual data, optimizing processes and driving significant improvements in your supply chains.

• Define Computer Vision and its core concepts (image processing, object detection, image classification).

• Grasp the fundamental techniques used in CV applications (image segmentation, feature extraction).

• Explore how deep learning revolutionized the field of Computer Vision.

• Identify real-world applications of CV in Supply Chain Management (e.g., automated product inspection, inventory management, warehouse automation).

• Understand the challenges and limitations of CV technology.

1. Introduction to Computer Vision

• What is Computer Vision? Historical development and its impact on various industries.

• Demystifying the "seeing" process: Image acquisition, processing, and analysis.

• Core CV tasks: Image Classification (identifying objects), Object Detection (locating objects), Image Segmentation (grouping pixels).

• Hands-on Activities: Exploring image processing techniques using online tools.

• Case Studies: Exploring early applications of CV in barcode reading and automated inspection in SCM.

2. Deep Learning and the CV Revolution

• Introduction to Deep Learning: Artificial Neural Networks and their role in CV advancements.

• Convolutional Neural Networks (CNNs): The workhorse of modern CV applications.

• Understanding how CNNs learn from image data (filters, pooling layers).

• Hands-on Activities: Exploring pre-trained CNN models for image classification tasks.

• Case Studies: How deep learning empowers advanced CV applications in defect detection and anomaly recognition for quality control.

3. CV Applications in SCM and Beyond

• Exploring CV applications in warehouse automation: Automated Picking and Stocking (APS) systems.

• Inventory management with CV: Real-time tracking and automated stock level monitoring.

• Beyond the warehouse: CV for optimizing transportation and logistics (e.g., package inspection, damage detection).

• Discussion on the future of CV in SCM: Robotics, predictive maintenance, and intelligent supply chains.

• Course Wrap-up: Addressing limitations and ethical considerations surrounding CV implementation.

• Strong understanding of linear algebra and calculus

• Proficiency in programming with Python and libraries such as NumPy and Matplotlib

• Familiarity with basic machine learning concepts and techniques