Final Product Progress over the Spring Break!

During my Spring Break, I was able to understand the theory behind convolutional neural networks through the guidance of my mentor. I was able to understand the different functions behind convolutional neural networks such as max pooling (taking the biggest features of the image), convolutional filters (filters that reduce the size of the image for easier analysis), stride (a factor that changes how many pixels of the image are analyzed and reduced by convolutional filters), and dot products (a product of each value in a certain frame multiplied). This helped me really strengthen my overall understanding of convolutional neural networks and how I could integrate them as a solution for my hand gestures recognition project.

I also was able to view some complications regarding my project such as the complexity to integrate my project in an usable form as I would need to have a deep understanding of OS systems if I want to have this feature available to device users at all times. Furthermore, there would be a need to understand how the model can perform a function by recognizing hand gestures as the software will need access to other apps as well as it will need to be well integrated with the functions of those apps. I think looking at several examples and tutorials over hand gestures recognition, machine learning model integration with apps, and how the computer science works behind this idea should help guide me to complete my final product successfully.

So see you next week, same time, same place.