Developed characterization and similarity measures for digraph-based complexes and applied them to iPDC brain networks to examine higher-order topology changes from pre-ictal to ictal to post-ictal phases in epilepsy.
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A method for incremental semantic class discovery that builds a segmented 3D map from RGBD frames and identifies new classes from unlabeled coherent regions, achieving 10.7 Hz updates on NYUDv2.
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Towards a Quantitative Theory of Digraph-Based Complexes and its Applications in Brain Network Analysis
Developed characterization and similarity measures for digraph-based complexes and applied them to iPDC brain networks to examine higher-order topology changes from pre-ictal to ictal to post-ictal phases in epilepsy.
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Incremental Class Discovery for Semantic Segmentation with RGBD Sensing
A method for incremental semantic class discovery that builds a segmented 3D map from RGBD frames and identifies new classes from unlabeled coherent regions, achieving 10.7 Hz updates on NYUDv2.