This week, I worked on the ethics assignment. Also, I have now established the initial training framework for the ML model. For the image dataset, I finalized comparisons between three models: ResNet18, ResNet50, and MobileNetV2. I am now evaluating their performance on two image datasets: PlantDoc and the houseplant/greyscale dataset I sourced online. I also set up a system to log the performance of each model to allow for a more comprehensive comparison. For the sensor data, I ran additional tests with various classifiers. All classifiers (SVM, Random Forest, etc.) returned 100% accuracy. Since we haven’t gathered sufficient data yet, I decided to delay final classifier selection until more data is collected from our own plant sensors and the late fusion stage is trained.
I am currently on schedule with the project timeline. The training results for the image models are looking promising, and I was able to complete the deliverables for this week successfully.
Next Week’s Deliverables:
- Finalize Model Selection: Based on the training results, which I expect to get in the next day, I plan to finalize the selection of the ML models (for image data)
- RPi Camera Setup: I will set up the Raspberry Pi camera and begin collecting our own image data.