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About Deep Learning-Based Feature Extraction in Iris Recognition: Use Existing Models, Fine-Tune or Train From Scratch?
This document explores using deep learning techniques to extract effective features for iris recognition. Specifically, it examines whether to use pre-trained models from other domains, fine-tune existing models on iris data, or train models from scratch on iris data. The authors use a ResNet-50 model trained five different ways to extract features from iris images and evaluate classification accuracy. They find that fine-tuning a pre-trained model on over 360,000 iris images achieves the best performance, outperforming both pre-trained and from-scratch trained models.
Detailed Information
| Author: | ['Satyanarayan Gupta'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 9 |
| Language: | English |
| Format: | |
| Price: | FREE |
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