This week is the first week after spring break. The team has completed the live testing processes, looking at the results, we have decided to use the feature extraction approach for pin classification, as the CNN model for pin classification… Read More

This week we have begun our live testing process. This process collects a new dataset to be used in optimizing our models. While collecting new data, our latest models are run on each collected frame to immediately gauge our performance.… Read More

This week we made strides in our feature extraction approach. Determining the location of the multimeter probe tip in a frame has proven to be a challenge. This is due to the camera perspective changing slightly during use. This issue… Read More

Improvements have been made with deep learning model training workflow. Given that we have four separate datasets available to us, we now can declare which datasets to use for each of the train, validation, and testing sets for the model.… Read More

The team has finished up data collection, completing the second set of data to be used in training and testing. With that being completed, some preliminary testing has been done with the feature extraction approach for the pin classification. Before… Read More

The team has been working hard to finish collecting our new dataset and further improve our two pin classification approaches. We plan to have the new dataset completed by the weekend. So far, we have 11 out of 15 plugs… Read More

In the past week we have made some more progress on our pin identification feature extraction technique. We have completed the first phase and have moved on to pin mapping. This is a step where we create a map of… Read More

We began making more progress on our pin classification using both deep learning and feature extraction. These two approaches are being experimented with and in the next two weeks we will choose one to develop for rest of the semester.… Read More

This week the team began working again for the beginning of the second semester of IPPD. During the break, we made critical model improvements that helped us gain a lot of confidence in our approach for plug classification. We are… Read More