2022 IFIP/IEEE 30th International Conference on Very Large Scale Integration (VLSI-SoC) 2022
DOI: 10.1109/vlsi-soc54400.2022.9939582
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P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking

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Cited by 10 publications
(1 citation statement)
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“…In addition, a processing-in-pixel-in-memory paradigm for CIS reported an 11× energy-delay product (EDP) improvement on the Visual Wake Words (VWW) dataset (Datta et al, 2022c ). Follow-up works by the same authors have demonstrated 5.26 × and 3.14 × reduction in energy consumption on hyperspectral image recognition (Datta et al, 2022e ) and multi-object tracking in the wild (Datta et al, 2022d ), respectively. In summary, due to the embedded pixel-level processing elements, the in-pixel processing approach can outperform energy and throughput compared to in-sensor and near-sensor processing solutions.…”
Section: Introductionmentioning
confidence: 96%
“…In addition, a processing-in-pixel-in-memory paradigm for CIS reported an 11× energy-delay product (EDP) improvement on the Visual Wake Words (VWW) dataset (Datta et al, 2022c ). Follow-up works by the same authors have demonstrated 5.26 × and 3.14 × reduction in energy consumption on hyperspectral image recognition (Datta et al, 2022e ) and multi-object tracking in the wild (Datta et al, 2022d ), respectively. In summary, due to the embedded pixel-level processing elements, the in-pixel processing approach can outperform energy and throughput compared to in-sensor and near-sensor processing solutions.…”
Section: Introductionmentioning
confidence: 96%