Late Breaking Results: Less Sense Makes More Sense: In-Sensor Compressive Learning for Efficient Machine Vision

Integrating deep learning and image sensors has significantly transformed machine vision applications. Yet, conventional highresolution image acquisition schemes enabled by imagers are energyinefficient for deep learning, as they involve excessive data quantization and transmission overhead. To addr...

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Veröffentlicht in:	2025 62nd ACM/IEEE Design Automation Conference (DAC) S. 1 - 2
Hauptverfasser:	Liang, Yiwen, Cao, Weidong
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 22.06.2025
Schlagworte:	Data compression Deep learning Design automation Energy conservation Feature extraction Image coding Image sensors Machine vision Optimization Quantization (signal)
Online-Zugang:	Volltext
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