MotiMem: Motion-Aware Approximate Memory for Energy-Efficient Neural Perception in Autonomous Vehicles: An Evidence Synthesis on Measurement Uncertainty And Sensitivity Analysis

This evidence-synthesis article examines resource-efficient autonomous perception through the focal contribution “MotiMem: Motion-Aware Approximate Memory for Energy-Efficient Neural Perception in Autonomous Vehicles” and nine author-disjoint, topically matched studies. The analysis is organized around measurement uncertainty and sensitivity analysis. Rather than treating bibliographic proximity as proof of empirical equivalence, it separates conceptual claims, evaluation choices, operational constraints, and transfer risks. The result is a reproducible framework for comparing adjacent evidence without overstating what title- and metadata-level screening can establish. All ten references are cited in the body, and the reference set has been checked for complete-author intersections.

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