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- Live Classifier: Train custom classes with labeled examples, test classification - Few-Shot Learning: 3-class system (A/B/C) with drag-drop training - Incremental Learning: Positive/negative examples with prototype visualization - Feedback Learning: Track predictions and accuracy over time - Memory Bank: View stored embeddings, export/import as JSON - Camera Training: Train using webcam with single/auto-capture modes All demos use real CNN embeddings (512-dim) with prototypical networks for classification. Includes cosine similarity scoring and confidence bars. Co-Authored-By: claude-flow <ruv@ruv.net> |
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| index.html | ||
| ruvector_cnn_wasm.js | ||
| ruvector_cnn_wasm_bg.wasm | ||