Week 12: Aftermath (Reflection Post)

Hi everyone! Thank you to those who made it this far in my project! This is officially the end of my senior project at the 12th week. In this post, I’ll do a reflection on what I did over the senior project, what my experience was like, and the impacts and further research directions for my project.

Reflection

Despite the fact that I consider myself a person decently-versed in computer science and going to study electrical and computer engineering, I felt much less confident about my experience in AI compared to my peers. I had only done AI projects in classes. Participating in the senior project allowed me to gain hands-on experience building and training AI models (almost) from scratch. There’s a lot more of going through the process of encountering problems and finding a solution for it. For example, my failures with the normal U-Net leading me to investigate the Siamese U-Net.

As a person who can’t learn new information unless it is shoved down my throat, challenging myself to understand the models I’m using to the best of my ability was very rewarding. I learned to read research papers and actually digest it, and how to reverse-engineer AI models’ code implementation to adjust its architecture. Working with my internal and external advisors gave me a balance of independent solution-seeking and guidance, which I’m really grateful for.

No Regrets… Right?

I’m glad that my research project can end on a positive note. I learned a lot about different segmentation models, and I’m happy with the results I got. However, there are things looking back on that might have made this better. For one, I almost neglected my DeepLab V3+ model because I spent a long time fixating on the U-Net, so I wasn’t able to bring it up to its full potential. Same with the SegFormer, where despite it’s good performance, I couldn’t implement the changes I wanted to with it at the end. I thought the scope I chose was manageable, but I didn’t account for how much I’ll expand on it while I worked on it.

Impact and Future Work

As for the project itself, my work allows me to create the groundwork for accomplishing similar tasks in remote sensing. It could be used for other disasters, like tornados, hurricanes, or floods, since the procedure for these are the same as for earthquakes. If I could continue with this project, I’d like to implement routing algorithms which prioritize damaged buildings for rescue teams to use. Another direction I’d like to take is to train models on satellite images captured in other spectral bands, where the buildings might reflect differently and make differences in damage levels easier to recognize.

Please look forward to the final presentation tomorrow, or the recording of it which I will post on Sunday!