UFO is a new publicly available hand-labeled dataset of 215 PlanetScope image chips from 14 urban flood events annotated for inundated and non-inundated areas, validated via segmentation model with 77.3 mean IoU and comparisons to existing water products.
Within-Camera Multilayer Perceptron DVS Denoising
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DeepSignature embeds digitally signed content-encoding watermarks via neural networks for robust image authentication, source attribution, and latent-space tamper localization.
Strait cuts high-priority deadline violations in ML inference serving by 1-11 percentage points through contention modeling and priority scheduling under high GPU load.
SNNF uses an event-based binary image and single-layer SNN to achieve 0.89 AUC in distinguishing signal from noise in DVS while using only 11-40% of the resources of prior filters.
citing papers explorer
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Urban Flood Observations (UFO): A hand-labeled training and validation dataset of post-flood inundation
UFO is a new publicly available hand-labeled dataset of 215 PlanetScope image chips from 14 urban flood events annotated for inundated and non-inundated areas, validated via segmentation model with 77.3 mean IoU and comparisons to existing water products.
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DeepSignature: Digitally Signed, Content-Encoding Watermarks for Robust and Transparent Image Authentication
DeepSignature embeds digitally signed content-encoding watermarks via neural networks for robust image authentication, source attribution, and latent-space tamper localization.
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Strait: Perceiving Priority and Interference in ML Inference Serving
Strait cuts high-priority deadline violations in ML inference serving by 1-11 percentage points through contention modeling and priority scheduling under high GPU load.
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SNNF: An SNN-based Near-Sensor Noise Filter for Dynamic Vision Sensors
SNNF uses an event-based binary image and single-layer SNN to achieve 0.89 AUC in distinguishing signal from noise in DVS while using only 11-40% of the resources of prior filters.