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- W4317927959 abstract "Cyber-physical systems are starting to adopt neural network (NN) models for a variety of smart sensing applications. While several efforts seek better NN architectures for system performance improvement, few attempts have been made to study the deployment of these systems in the field. Proper deployment of these systems is critical to achieving ideal performance, but the current practice is largely empirical via trials and errors, lacking a measure of quality. Sensing quality should reflect the impact on the performance of NN models that drive machine perception tasks. However, traditional approaches either evaluate statistical difference that exists objectively, or model the quality subjectively via human perception." @default.
- W4317927959 created "2023-01-25" @default.
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- W4317927959 date "2022-11-06" @default.
- W4317927959 modified "2023-09-30" @default.
- W4317927959 title "SQEE" @default.
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- W4317927959 doi "https://doi.org/10.1145/3560905.3568534" @default.
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