This week, I collected and recorded a lot of data on the accuracy of our recycling system. Specifically, I collected data on the accuracy of the sensor classifier, the image classifier, and the overall classifier. I conducted 100 trials per material for our overall classifier for various different items of the same material classification. So, 100 trials were conducted for each material category which includes PET plastic, HDPE plastic, metal, glass, paper, cardboard, and trash. In addition, for the individual testing of the sensor and image classifiers, I conducted 50 trials per material category for both classifiers separately. Here I have attached the full data sheet with all of the recorded accuracy numbers: Data. I also recorded the accuracy of our ResNet model per epoch during its training and graphed the results here.
My progress is on track.
In the next week, I hope to continue to improve our overall accuracy with the rest of my team and help Jessica prepare for our Final Presentation next week. I also plan to work with my team to start making videos of our functioning system for our video demo coming up.