CircleID introduces a controlled dataset of 46,155 circles from 66 writers and 8 pens, with competition results showing top accuracies of 64.8% for open-set writer identification and 92.7% for pen classification.
IEEE transactions on pattern analysis and machine intelligence43(10), 3614–3631 (2020)
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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FedFMX adds Fisher-routed expert selection and routing-aware regularization to federated class-incremental learning and proves an O(T^{-1}) convergence rate.
DMDSC adapts class-specific margins dynamically by label frequency in deep simplex classifiers to improve open-set recognition on imbalanced medical image datasets.
citing papers explorer
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ICDAR 2026 Competition on Writer Identification and Pen Classification from Hand-Drawn Circles
CircleID introduces a controlled dataset of 46,155 circles from 66 writers and 8 pens, with competition results showing top accuracies of 64.8% for open-set writer identification and 92.7% for pen classification.
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Fisher-Routed Mixture of Experts for Federated Class-Incremental Learning
FedFMX adds Fisher-routed expert selection and routing-aware regularization to federated class-incremental learning and proves an O(T^{-1}) convergence rate.
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DMDSC: A Dynamic-Margin Deep Simplex Classifier for Open-Set Recognition on Medical Image Datasets
DMDSC adapts class-specific margins dynamically by label frequency in deep simplex classifiers to improve open-set recognition on imbalanced medical image datasets.