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Deep neural network compression through interpretability-based filter pruning

Research article (Pattern Recognition, 2021) · cited 38× · AI/ML
academia openalex:W3170968300
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Deep neural network compression through interpretability-based filter pruning

Summary

Deep neural network compression through interpretability-based filter pruning is a scholarly article[1].

Key Facts

  • Deep neural network compression through interpretability-based filter pruning's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Deep neural network compression through interpretability-based filter pruning. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-neural-network-compression-through-interpretability-based-filter-pruning
MLA “Deep neural network compression through interpretability-based filter pruning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-neural-network-compression-through-interpretability-based-filter-pruning.
BibTeX @misc{4ortxyz_deep-neural-network-compression-through-interpretability-based-filter-pruning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep neural network compression through interpretability-based filter pruning}}, year = {2026}, url = {https://4ort.xyz/entity/deep-neural-network-compression-through-interpretability-based-filter-pruning}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep neural network compression through interpretability-based filter pruning — https://4ort.xyz/entity/deep-neural-network-compression-through-interpretability-based-filter-pruning (retrieved 2026-05-24)

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