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Challenges in Energy-Efficient Deep Neural Network Training with FPGA

Research article (2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020) · cited 27× · AI/ML
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Challenges in Energy-Efficient Deep Neural Network Training with FPGA

Summary

Challenges in Energy-Efficient Deep Neural Network Training with FPGA is a scholarly article[1].

Key Facts

  • Challenges in Energy-Efficient Deep Neural Network Training with FPGA's instance of is recorded as scholarly article[2].

Related Entities

Mei-Ling Shyu Shu-Ching Chen

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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). Challenges in Energy-Efficient Deep Neural Network Training with FPGA. Retrieved May 24, 2026, from https://4ort.xyz/entity/challenges-in-energy-efficient-deep-neural-network-training-with-fpga
MLA “Challenges in Energy-Efficient Deep Neural Network Training with FPGA.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/challenges-in-energy-efficient-deep-neural-network-training-with-fpga.
BibTeX @misc{4ortxyz_challenges-in-energy-efficient-deep-neural-network-training-with-fpga_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Challenges in Energy-Efficient Deep Neural Network Training with FPGA}}, year = {2026}, url = {https://4ort.xyz/entity/challenges-in-energy-efficient-deep-neural-network-training-with-fpga}, note = {Accessed: 2026-05-24}}
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