Computer Science Facial Recognition: Scene Detection (Faster R-CNN) There is a lot of mysticism around Facial Recognition. On films it is seen as an ominous, powerful, and complicated technology. It, now that I have explored this field slightly,
Astronomy Imaging Atmospheric Cherenkov Telescopes/Technique (IACT) As I was going through the catalog of UCI Machine Learning Repository, a certain data set caught my eye, it's name is MAGIC Gamma Telescope Data Set. After closer inspection, It was a data set created via Monte Carlo simulation of what would be read from a Gamma Telescope.
Physics Finding the Higgs boson w/ Shallow Neural Networks Recently, I started work on a C++ library with the purpose of creating easily creating and training Neural Networks.
Mathematics Error Functions, Stochastic Gradient Descent, & Backpropagation oth the Stochastic Gradient Descent and Backpropagation are important concepts to understand when studying Neural Networks. Stochastic Gradient Descent optimizes the weights and Backpropagation finds the gradient of the error function quickly.
Neural Networks Structure, Feedforward Neural Networks A lot of times, Neural Networks are talked about in a purely conceptual way, leaving lea way for someone, who is trying to understand it's mechanics, room for misunderstandings. IntroHere,
Astronomy Galaxy Image Classification using Convoluational Neural Networks SDSS's 14th data release, it amounts to over 125 terabytes of information. There arises the problem of visually classifying such a large amount of data. For this, Artificial Neural Networks (ANNs) are great tools.
