Support-weighted partial recentering of maxmin seeds using halfspace depth yields consistent geometric improvement over standard maxmin in planar benchmarks while preserving thresholded H1 summaries.
Shape matching and object recognition using shape contexts.IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(4):509–522
2 Pith papers cite this work. Polarity classification is still indexing.
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Transfer learning with fine-tuned AlexNet achieves 98% accuracy classifying smartphone e-waste into 12 classes on a small dataset via hyperparameter tuning and augmentation.
citing papers explorer
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Local Depth-Based Corrections to Maxmin Landmark Selection for Lazy Witness Persistence
Support-weighted partial recentering of maxmin seeds using halfspace depth yields consistent geometric improvement over standard maxmin in planar benchmarks while preserving thresholded H1 summaries.
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Transfer learning-based method for automated ewaste recycling in smart cities
Transfer learning with fine-tuned AlexNet achieves 98% accuracy classifying smartphone e-waste into 12 classes on a small dataset via hyperparameter tuning and augmentation.