Cloud inference can match or exceed on-device performance for latency-sensitive control in distributed CPS when high-throughput resources amortize network and queueing delays.
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3 Pith papers cite this work. Polarity classification is still indexing.
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FMC-DETR proposes a frequency-decoupled fusion framework with WeKat backbone, MDFC coordination, and CPF fusion modules that claims state-of-the-art results on remote sensing object detection benchmarks.
FSDETR enhances RT-DETR with SHAB, DA-AIFI, and FSFPN blocks to improve small-object detection, reporting 13.9% APS on VisDrone 2019 and 48.95% AP50 on TinyPerson using 14.7M parameters.
citing papers explorer
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Cloud Is Closer Than It Appears: Revisiting the Tradeoffs of Distributed Real-Time Inference
Cloud inference can match or exceed on-device performance for latency-sensitive control in distributed CPS when high-throughput resources amortize network and queueing delays.
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FMC-DETR: Frequency-Decoupled Multi-Domain Coordination for Aerial-View Object Detection
FMC-DETR proposes a frequency-decoupled fusion framework with WeKat backbone, MDFC coordination, and CPF fusion modules that claims state-of-the-art results on remote sensing object detection benchmarks.
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FSDETR: Frequency-Spatial Feature Enhancement for Small Object Detection
FSDETR enhances RT-DETR with SHAB, DA-AIFI, and FSFPN blocks to improve small-object detection, reporting 13.9% APS on VisDrone 2019 and 48.95% AP50 on TinyPerson using 14.7M parameters.