Design and develop a machine learning algorithm that can process high resolution video content
Student teams will be given 24 hours of time to hack within a 30-hour event to design and develop a machine learning algorithm that can process high resolution video content. Student teams of 3-5 can either be assembled ahead of time or will be matched at the start of the event. Teams will be given a set of labeled images to train their machine learning algorithms, with the intent of extracting data features from the images and using these engineered features to build a model that can predict and label additional images with relevant tags. To win the competition, teams will need to process this video as it streams in nearly real-time, taking into consideration accuracy and fluid prediction syncing. Furthermore, the student models will need to display predicted tags alongside the video in a novel way which improves the user experience. Students will have a chance to network with FOX leadership. In addition to the knowledge acquired by students competing in the challenge, workshops will be facilitated throughout the event to teach students the skills necessary to be competitive.
$2,600 in prizes
FOX Data Summit (5)
1st place; Demo and present the winning model at the FOX Data Summit in February, tour of the FOX lot, travel and accommodations included.
Apple Watch (5)
Amazon Fire Cube (5)
Submitting to this hackathon could earn you:
- Any Arizona State University student is welcome to participate. Whether you’re an undergraduate, masters student, or Ph.D. candidate, you’re welcome!
- A team can have between 3 and 5 members.
Project Submissions Judging
The projects will be judged thoroughly on the concepts of innovation and design as well as the effectiveness of the program.
- Machine Learning/AI