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An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet

Research article (Mathematical Problems in Engineering, 2020) · cited 36× · AI/ML
academia openalex:W3096271249
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An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet

Summary

An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet is a scholarly article[1].

Key Facts

  • An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet's instance of is recorded as scholarly article[2].

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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). An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-electronic-component-recognition-algorithm-based-on-deep-learning-with-a-faster-squeezenet
MLA “An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-electronic-component-recognition-algorithm-based-on-deep-learning-with-a-faster-squeezenet.
BibTeX @misc{4ortxyz_an-electronic-component-recognition-algorithm-based-on-deep-learning-with-a-faster-squeezenet_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet}}, year = {2026}, url = {https://4ort.xyz/entity/an-electronic-component-recognition-algorithm-based-on-deep-learning-with-a-faster-squeezenet}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet — https://4ort.xyz/entity/an-electronic-component-recognition-algorithm-based-on-deep-learning-with-a-faster-squeezenet (retrieved 2026-05-24)

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