AI RESEARCH
SatReg: Regression-based Neural Architecture Search for Lightweight Satellite Image Segmentation
arXiv CS.CV
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ArXi:2604.10306v1 Announce Type: new As Earth-observation workloads move toward onboard and edge processing, remote-sensing segmentation models must operate under tight latency and energy constraints. We present SatReg, a regression-based hardware-aware tuning framework for lightweight remote-sensing segmentation on edge platforms. Using CM-UNet as the teacher architecture, we reduce the search space to two dominant width-related variables, profile a small set of student models on an NVIDIA Jetson Orin Nano, and fit low-order surrogate models for mIoU, latency, and power.