Day 9
This morning we looked at some of the interns' abstracts. This showed me that I should probably edit my own abstract. It's really quite difficult to maintain brevity (recommended <100 words) while trying to include everything I think I should. This morning's peer review helped me sort it out a bit more though.
Today was Ron's first day back, and he had a lot of catching up to do with Angelina, Marc, and I. He showed me how to use RIT Libraries and Google Scholar to find papers about semi-supervised models to compare our own performance to. This task basically took up all of my time today, and I'm likely going to do something similar tomorrow. The process is really tedious, but also clearly necessary for the paper I am helping Ron with. I'd compare it to trying to find a needle in a haystack, but finding a handful of paperclips instead. Not quite what you're looking for, but it'll have to do until you find a better one.
As promised from last time, I have another data visualization. Each "pixel" in the Pavia University image consists of 103 values, representing how much the material at said pixel reflects each wavelength. These values can be plotted like so, and it can be pretty easy to make some generalizations about the given material.
The following image shows 9 graphs, each representing one of Pavia University's 9 classes. These plots can be thought of as hundreds or thousands of the above plot stacked on top of each other. This gives a pretty good idea of the general reflectance of each material and more importantly how varied they can be.
Today was Ron's first day back, and he had a lot of catching up to do with Angelina, Marc, and I. He showed me how to use RIT Libraries and Google Scholar to find papers about semi-supervised models to compare our own performance to. This task basically took up all of my time today, and I'm likely going to do something similar tomorrow. The process is really tedious, but also clearly necessary for the paper I am helping Ron with. I'd compare it to trying to find a needle in a haystack, but finding a handful of paperclips instead. Not quite what you're looking for, but it'll have to do until you find a better one.
As promised from last time, I have another data visualization. Each "pixel" in the Pavia University image consists of 103 values, representing how much the material at said pixel reflects each wavelength. These values can be plotted like so, and it can be pretty easy to make some generalizations about the given material.
The following image shows 9 graphs, each representing one of Pavia University's 9 classes. These plots can be thought of as hundreds or thousands of the above plot stacked on top of each other. This gives a pretty good idea of the general reflectance of each material and more importantly how varied they can be.
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