Computer vision
Computer vision research: learning level set image segmentation with echo state networks and recurrent models, plus an object following robot.
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4 results for “Computer Vision”
Follow me Turtle Bot Project
Our follow me turtle bot project, used python and ROS to design turtle-bot that follows an object. This was done at the Witwatersrand University school of Computer Science and Applied Mathematics.
Echo state networks for level set image segmentation
MSc research at Wits: can recurrent models learn the iterative evolution of a level set segmentation? Echo state networks against trained RNN, LSTM and GRU.
Learning Level Set Method by Echo State Network for Image Segmentation
Studies echo state networks as a cheaper alternative to recurrent networks trained by backpropagation, applied to learning variational level set image segmentation as a spatiotemporal, data driven method. Five convolutional architectures were compared (ESN, RNN, GRU, LSTM and a 3D CNN) on four datasets; the GRU and LSTM variants performed best. The ESN performed poorly, which the dissertation attributes largely to the reservoir's leaking rate and spectral radius.