Delaunay triangulation
PulseAugur coverage of Delaunay triangulation — every cluster mentioning Delaunay triangulation across labs, papers, and developer communities, ranked by signal.
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Graph Neural Networks Enhance Football Tactical Analysis
Researchers have developed a novel framework using graph neural networks (GNNs) combined with a sequential model to classify tactical phases in football matches on a second-by-second basis. This approach, detailed in a …
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POLARIS system offers training-free audio fingerprinting
Researchers have developed POLARIS, a novel training-free audio fingerprinting system. This system utilizes landmarks from a saliency field and groups them using Delaunay triangulation to create sparse fingerprints. POL…
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New algorithm achieves differential sensitivity in image permutation
Researchers have developed a new algorithm called Triangular Content-Aware Permutation (TCA) that challenges the long-held assumption that pixel permutation alone cannot achieve differential sensitivity in image process…
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New DTIF framework uses Delaunay triangulation for forest mapping
Researchers have developed DTIF, a new framework for robust loop closure detection in complex forest environments. This system utilizes Delaunay triangulation of tree trunks to create a compact scene representation, ove…
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AI system uses geometric normalization for accurate pneumonia and COVID-19 detection in X-rays
Researchers have developed an automated system for identifying pneumonia and COVID-19 in chest X-rays by geometrically normalizing the lung region. The system employs a ResNet-18 model for landmark detection, followed b…
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Graph Neural Networks enhanced with proximity graphs for dust emission forecasting
Researchers have developed a novel method to enhance Graph Neural Networks (GNNs) for dust source emission forecasting by incorporating proximity graphs. These graphs, including Delaunay triangulation, Gabriel graph, k-…