HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology

Research article (ACM Transactions on Embedded Computing Systems, 2021) · cited 10× · AI/ML

academia openalex:W3170004439

Press Enter · cited answer in seconds

HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology

Summary

HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology is a scholarly article^[1].

Key Facts

HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology's instance of is recorded as scholarly article^[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

[2] ↑ HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology — instance of (P31): scholarly article. wikidata.org.

Class ancestry

[1] ↑ HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology is an instance of scholarly article (scholarly article) [P31, primary]. Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA

4ort.xyz Knowledge Graph. (2026). HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology. Retrieved May 24, 2026, from https://4ort.xyz/entity/hw-flowq-a-multi-abstraction-level-hw-cnn-co-design-quantization-methodology

MLA

“HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hw-flowq-a-multi-abstraction-level-hw-cnn-co-design-quantization-methodology.

BibTeX

@misc{4ortxyz_hw-flowq-a-multi-abstraction-level-hw-cnn-co-design-quantization-methodology_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology}}, year = {2026}, url = {https://4ort.xyz/entity/hw-flowq-a-multi-abstraction-level-hw-cnn-co-design-quantization-methodology}, note = {Accessed: 2026-05-24}}

LLM prompt

According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): HW-FlowQ: A Multi-Abstraction Level HW-CNN Co-design Quantization Methodology — https://4ort.xyz/entity/hw-flowq-a-multi-abstraction-level-hw-cnn-co-design-quantization-methodology (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/hw-flowq-a-multi-abstraction-level-hw-cnn-co-design-quantization-methodology · Last refreshed: May 24, 2026