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About Transfer Learning
This document summarizes a study that used transfer learning from deep convolutional neural networks to develop an automated system for fracture detection on plain radiographs. The study: 1) Used a pre-trained Inception v3 network and re-trained just the top layer to classify lateral wrist radiographs as either "fracture" or "no fracture". 2) Trained the model on over 11,000 images from an initial set of 1,389 radiographs, achieving good performance with an AUC of 0.954 on a test set. 3) Demonstrated that transfer learning from pre-trained CNNs is a promising approach for fracture detection on radiographs that requires only a moderate sized dataset.
Detailed Information
Author: | ['Adah Ene'] |
---|---|
Publication Year: | 2021 |
Pages: | 7 |
Language: | English |
Format: | |
Price: | FREE |
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