NYCDSA | Applying Deep-learning to Solving Autonomous Driving
Join us online on Friday, Aug 20th at 4:00 PM EST to learn about Tyrone’s capstone project about human attentiveness in autonomous driving
Inspired by the problem of autonomous driving, Tyrone focused on one aspect of it: human attentiveness, which is required at all times when operating sub-level 4 autonomous vehicles (https://www.synopsys.com/automotive/autonomous-driving-levels.html). He gathered, prepared, and labeled 10K+ images and fine-tuned the top layers of a pre-trained ResNet-152 model to classify attentiveness in images, videos accurately, and live feed. He also produced an app that allows anyone to get their videos labeled and scored with an “Attention Score.”
Join us on August 20th, at 4 PM ET, and learn about Tyrone’s capstone project.
Learn what he has learned at the Academy and how his project has a host of real-world applications outside of improving driver attentiveness.
Employers can implement attention monitoring to increase workplace productivity.
Video chat platforms like Zoom can incorporate it as a feature.
Students can use it to fine-tune their workflow.
There are many possibilities.