This week was focused on clearly establishing the boundaries of our project and presenting our proposal during 18-500 class time.Ā As such, this week was primarily focused on research and preparing for implementation. Seeing our peers’ project proposals was a useful way to reflect on the strong and weak points of our own project planning.Ā I’m most exicted to focus on the integration and aplication of our various project pieces.Ā Ultimately, we need to connect out hardware and ML algorithms to a functional display that can be easily navigated by a user. To broden the scope of what our project can be applied to, I’ve spent significant time looking into the possible input and output connection points we can easily integrate early on to ensure we’ll be able to smoothly connect our various pieces together when finishing our project.
Moreover, my teammates have a deeper understanding of machine learning in practice than I do so I’ve also spent time time this week continuing to familliarize myself with the process of training and optimizing an LLM and CV neural network. Since training any ML algorithm is a substantial task, I’ve focused on learning more of the the grammar rules ASL uses to begin the process of selecting hyperparameters or otherwise tuning our algorithms to best meet our needs.
Currently, my progress is on schedule as we’re laying the groundwork to ramp up training and processing our datasets, as outlined in ourĀ Gantt Chart below.
In the next week, I hope to continue researching the aformentioned topics and collaborate with my teammates to establish the division of labor for the week. Developing a human-pose estimationĀ pre-processing model will be the software end’s next main step and establishing a clear roadmap for achieving our project objectives will be necessary.