Welcome! This is my summer internship work page during my time at the Marine Physical Laboratory at the Scripps Insitution of Oceanography under Doctor Jules Jaffe and his PhD students. My research is primarily focused on applying computer vision and machine learning techniques to efficiently analyze the big data that is provided through their in situ optical underwater imaging systems.
Click here to view my latest work
We have chosen to experiment with three source domains to test our hypothesis on utilizing a different source domain to boost classification performance and reduce the amount of effort to train the classifiers. Below are our source domains:
- SPCBench
- SPCInsitu
- SPCombo
We will evaluate these three source domains' experiments by testing them on our target domain dataset, which will ultimately provide us an accurate representation of how these classifiers fare in a realistic deployment environment.
Below is a presentation & report of all my experiments and their results to better explain my research.
Mpl summer 2017 project report
The eval.py and train_alexnet.py script are definitive python scripts that are robust enough to use for all of the source domain experiments, as well as evaluating the target domain. More information regarding how to navigate through these scripts will come!
Keep a look out for the conference release of this research at the 2018 Ocean Sciences Meeting from February 11-16th
Feel free to contact me if you'd like to hear about my research. My contact information, as well as my resume and LinkedIn, can be found below
Kevin Le