Understanding convolutional neural network classification errors caused by image quality degradation

Page King; R. John Koshel

doi:10.1117/12.3027143

3 October 2024 Understanding convolutional neural network classification errors caused by image quality degradation

Page King, R. John Koshel

Author Affiliations +

Proceedings Volume 13138, Applications of Machine Learning 2024; 131380F (2024) https://doi.org/10.1117/12.3027143
Event: Optical Engineering + Applications, 2024, San Diego, California, United States

Abstract

Robustness to image quality degradations is critical for developing Convolutional Neural Networks (CNNs) for real-world image classification. This paper advances previous analysis of how optical aberrations and optical scatter degrade classification performance by exploring how they cause classification errors to manifest within CNN layers.

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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Page King and R. John Koshel "Understanding convolutional neural network classification errors caused by image quality degradation", Proc. SPIE 13138, Applications of Machine Learning 2024, 131380F (3 October 2024); https://doi.org/10.1117/12.3027143

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