Tutorial C
|
Introduction to Artificial Intelligence Computer Vision Models |
Fees
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$250 USD each |
Date
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Monday – February 24, 2025 |
Time
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8:00 AM – 11:30 AM PT |
| Overview |
This hands-on tutorial is designed to provide participants with practical experience in computer vision, focusing on real-time, hands-on object detection and classification. Participants will be provided with an account to access a web-accessible virtual machine to explore the fundamentals of image processing, neural networks, and computer vision applications, empowering them to build and deploy their own projects. The course will also highlight important lessons about operating Tactical Edge environments where there are often constraints on the size, weight, power, and cost (SWaP-C) of devices. Attendees will learn the basics of setting up a Jupyter Notebook for computer vision tasks to implement advanced neural network models for real-time object detection. Through a blend of lectures and hands-on exercises, they will learn how to manipulate images, apply pre-trained neural networks, and optimize object detection models. By the end of the tutorial, they will have a functional understanding of computer vision techniques and the ability to deploy object detection systems. |
| Instructor |
Cole Frank, Jonathan Frederick, Software Engineering Institute |
Biography
|
Cole Frank Cole is an Associate AI Workforce Development Engineer in SEI’s AI Division. His work is primarily focused on how to effectively upskill the federal AI workforce. He holds an M.S. in Computational
Analysis and Public Policy from the University of Chicago. Prior to graduate school, he worked as a
macroeconomic analyst at the Council on Foreign Relations and AllianceBernstein.Jonathan Frederick is a workforce development team lead in the AI Division within the Software Engineering Institute (SEI) at Carnegie Mellon University (CMU). He has managed various projects capturing and delivering on Department of Defense stakeholder requirements since returning to the SEI in 2022. Jonathan previously worked for Recorded Future from 2020 until 2022. At Recorded Future, he established partnerships, contracts, schedules, and deliverables for all instructor-led courses held globally. In the previous ten years when he was at the SEI, he developed cyber courseware and exercises for the Department of Defense and Department of Homeland Security. |
Description of Intended Audience and Recommended Prerequisites
|
This tutorial is an introduction and there are no recommended prerequisites. |
What can Attendees Expect to Learn
|
Attendees will learn the basics of setting up a Jupyter Notebook for computer vision tasks to implement advanced neural network models for real-time object detection. Through a blend of lectures and hands-on exercises, they will learn how to manipulate images, apply pre-trained neural networks, and optimize object detection models. By the end of the tutorial, they will have a functional understanding of computer vision techniques and the ability to deploy object detection systems. |
