Since my current ANN experiments are moving forward rather slowly, I have spent some time preparing the final background chapter for my dissertation. I the course of doing so, I have among other things looked at COBWEB , which is one of the most well-known concept formation algorithms. Today, I want to share the basic idea behind COBWEB and its variants.
In my last blog post, I introduced my current research project: Learning to map raw input images into the shape space obtained from my prior study. Moreover, I talked a bit about the data set I used and the augmentation steps I took to increase the variety of inputs. Today, I want to share with you the network architecture which I plan to use in my experiments. So let’s get started.
In a previous mini-series of blog posts (see here, here, here, and here), I have introduced a small data set of 60 line drawings complemented with pairwise shape similarity ratings and analyzed this data set in the form of conceptual similarity spaces. Today, I will start a new mini-series about learning a mapping from images into these similarity spaces, following up on my prior work on the NOUN dataset (see here and here).
Since this is going to be my last blog post for this year, I’m going to use it for reflecting a bit on my academic life this year and for talking a bit about my plans for 2021.
Since I’m still working on background chapters for my dissertation and hence currently do not have to share any research updates, I’m going to focus today’s blog post on my teaching duties. More specifically, I’ll try to convince you that grading sheets are a useful tool for making your own grading process more structured and objective, as well as for providing students with valuable feedback. Continue reading “What are “grading sheets” and why do we need them?”