Now showing items 1-5 of 5

    • Emergent behavior in neuroevolved agents 

      Maresso, Brian (University of Wisconsin--Whitewater, 2018-11)
      Neural networks have been widely used for their ability to create generalized rulesets for a given set of training data. In applications where no such training data exists such as new video games, they are often overlooked ...
    • Modeling user behavior to construct counter strategies 

      Hyde, Gregory (University of Wisconsin--Whitewater, 2019-08)
      We are working on the development of an adaptive learning framework addressing covariate shift, experienced in Behavioral Cloning (BC). BC user-modeling is a technique in which user-data, taken from observing a user’s ...
    • A residual recurrent convolutional neural network for image superresolution with whole slide images 

      Lynch, Jesse (University of Wisconsin--Whitewater, 2019-04)
      Presented is a deep learning based computational approach to solve the problem of enhancing the resolution of images gained from commonly available low magnification scanners, also known as the image super-resolution (SR) ...
    • Sensorflow : Learning Through Motion 

      Ziebell, Nick; Abundez-Arce, Adrian; Johnson, Christopher R. (2018-04)
      We want to enable the user to use internet-connected (IoT) devices in order to learn any alphabet outside the typical classroom setting in an engaging way. Machine learning facilitates classifying any type of images by ...
    • Superresolution recurrent convolutional neural networks for learning with multi-resolution whole slide images 

      Bui, Huu Dat (University of Wisconsin--Whitewater, 2018-11)
      A recurrent convolutional neural network is supervised machine learning way to process images that has both properties of convolutional and recurrent networks. We propose Convolutional Neural Network (CNN) based approach ...