This repository provides CPU (OpenMP) and GPU (CUDA) implementations of Generalised Geodesic Distance Transform in PyTorch for 2D and 3D input data based on parallelisable raster scan ideas from [1].
Abstract: Euclidean distance transforms are fundamental in image processing and computer vision, with critical applications in medical image analysis and computer graphics. However, existing ...
Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...
NeuroKit2 is a Python Toolbox for Neurophysiological Signal Processing. The presented method is an adaptation of NeuroKit2 to simplify and automate computation of the various mathematical estimates of ...
Unsupervised learning is a class of machine learning that involves finding patterns in unlabeled data. And clustering is an unsupervised learning algorithm that finds patterns in unlabeled data by ...
The IMED is the Euclidean distance (ED) applied to a transformed version of an image or n-dimensional volume that has image-like correlation along axes. It solves some of the shortcommings of using ...
1 Department of Computer Science and Engineering, Oakland University (OU), Rochester, MI, USA. 2 Department of Electrical and Computer Engineering, Oakland University (OU), Rochester, MI, USA. The ...
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