pith:PPHZGVDF
Scensory: Real-Time Robotic Olfactory Perception for Joint Identification and Source Localization
Scensory enables robots to identify fungal species and localize sources from short VOC sensor readings using neural networks.
arxiv:2509.19318 v3 · 2025-09-11 · eess.SP · cs.RO
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Claims
Across five fungal species, Scensory achieves up to 89.85% species accuracy and 87.31% source localization accuracy under ambient conditions with 3-7s sensor inputs.
Temporal VOC dynamics encode both chemical and spatial signatures, which we decode through neural networks trained on robot-automated data collection with spatial supervision.
Scensory uses neural networks trained on robot-collected VOC time series to jointly identify fungal species and localize sources, reporting up to 89.85% species accuracy and 87.31% localization accuracy from short inputs under ambient conditions.
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| First computed | 2026-05-29T01:04:55.987015Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/PPHZGVDFDPUAZMY3QU6EM5PDB5 \
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Canonical record JSON
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