The main goal of this project is to leverage the YOLO framework to create an effective real-time object recognition algorithm that is focused on detecting drone swarms.

By the end of the project, students should submit a final report (along with any source materials such as code, etc) that demonstrates:

- Understanding of the current YOLO algorithm
- Methodologies and approaches to enhancing the YOLO algorithm to specifically detect drone swarms
- Providing source code in a proper software development environment as applicable

By the end of the project, students should submit a final report (along with any source materials such as code, workbooks, etc) that demonstrates:

• Understanding of the YOLO algorithms
• Methodologies and approaches to detecting drone swarms
• Outcomes and results for implementing the algorithm for the detection of drone swarms
• Recommended next steps for our organization

Bonus steps in the process would also include:

• Providing multiple versions of any potential solutions
• Suggestions for various camera hardware to best implement drone swarm detection taking into consideration range and synchronicity

Students will connect directly with us for mentorship throughout the project. We will be able to provide answers to questions such as:

• Current product understanding
• Current data set and guidance in navigating it
• Current industry standard approaches to ML and AI.
• Input on choices, problems or anything else the students might encounter
• Understanding of produce use cases for drone swarms