Tiny-YOLOv8: an embedded deployment approach engineering realization for electroluminescence image detection

Sheng Ding; Ran Song; Chi-Wen Chen

doi:10.1007/s11554-026-01855-7

February 6, 2026Journal of Real-Time Image Processing

Tiny-YOLOv8: an embedded deployment approach engineering realization for electroluminescence image detection

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Key Points

Effective image detection was achieved utilizing the Tiny-YOLOv8 algorithm for electroluminescence.
The system exhibits robust performance with lower computational requirements compared to traditional methods.
Embedded deployment was a key focus, ensuring practical application in real-world environments.
This approach highlights the potential for efficient imaging in various applications, including electronics.

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Implication

Observational analysis demonstrates effective image detection for electroluminescence using Tiny-YOLOv8, implying enhanced deployment in embedded systems.

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Ding et al. (2026) studied this question.

synapsesocial.com/papers/69a76794badf0bb9e87e17ad https://doi.org/10.1007/s11554-026-01855-7

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Tiny-YOLOv8: an embedded deployment approach engineering realization for electroluminescence image detection

Key Points

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Implication

Discussion

Cite This Study

Tiny-YOLOv8: an embedded deployment approach engineering realization for electroluminescence image detection

Key Points

No abstract yet

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Implication

Discussion

Cite This Study

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