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General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantization

Research article (IEEE Transactions on Neural Networks and Learning Systems, 2021) · cited 42× · AI/ML
CreativeWork academia

Facts

4 properties
Instance of
scholarly article[2]
Publication date
April 8, 2021as of 2026-09-23
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Source
OpenAlex
Edition
20260923 · as of 2026-09-23
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4ort-mint · openalex:20260923 · version not recorded
Published in
IEEE Transactions on Neural Networks and Learning Systemsas of 2026-09-23
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OpenAlex
Edition
20260923 · as of 2026-09-23
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4ort-mint · openalex:20260923 · version not recorded
Title
General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantizationas of 2026-09-23
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OpenAlex
Edition
20260923 · as of 2026-09-23
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4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 3
OpenAlex ID
W3150698441as of 2026-09-23
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Source
OpenAlex
Edition
20260923 · as of 2026-09-23
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4ort-mint · openalex:20260923 · version not recorded
DOI
10.1109/TNNLS.2021.3069886as of 2026-09-23
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Source
OpenAlex
Edition
20260923 · as of 2026-09-23
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not in the catalog
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4ort-mint · openalex:20260923 · version not recorded
PubMed publication ID
33830929as of 2026-09-23
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Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
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4ort-mint · openalex:20260923 · version not recorded

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Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Authored by 4
Chenglin Li, Hongkai Xiong, Junni Zou, Wenrui Dai
← Author of 4
Chenglin Li, Hongkai Xiong, Junni Zou, Wenrui Dai
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Summary

General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantization is a scholarly article[1].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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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). General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantization. Retrieved October 20, 2026, from https://4ort.xyz/entity/general-bitwidth-assignment-for-efficient-deep-convolutional-neural-network-quantization
MLA “General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantization.” 4ort.xyz Knowledge Graph, 4ort.xyz, 20 Oct. 2026, https://4ort.xyz/entity/general-bitwidth-assignment-for-efficient-deep-convolutional-neural-network-quantization.
BibTeX @misc{4ortxyz_general-bitwidth-assignment-for-efficient-deep-convolutional-neural-network-quantization_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantization}}, year = {2026}, url = {https://4ort.xyz/entity/general-bitwidth-assignment-for-efficient-deep-convolutional-neural-network-quantization}, note = {Accessed: 2026-10-20}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantization — https://4ort.xyz/entity/general-bitwidth-assignment-for-efficient-deep-convolutional-neural-network-quantization (retrieved 2026-10-20)

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