Utilising deep learning for classification of disease-related lung opacities through colourmap optimisation
Introduction: Existing deep learning models for lung opacity detection primarily focus on grayscale images, overlooking the potential benefits of colour map transformations. In this study, we address this gap by fine-tuning DarkNet-53 and ResNet-101 deep learning models using both grayscale and 16 d...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en en |
| Published: |
Universiti Putra Malaysia Press
2024
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/117714/7/117714_Utilising%20deep%20learning%20for%20classification.pdf http://irep.iium.edu.my/117714/18/117714_Utilising%20deep%20learning%20for%20classification_Scopus.pdf http://irep.iium.edu.my/117714/ https://medic.upm.edu.my/upload/dokumen/2024123014111401_MJMHS_0662.pdf |
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Internet
http://irep.iium.edu.my/117714/7/117714_Utilising%20deep%20learning%20for%20classification.pdfhttp://irep.iium.edu.my/117714/18/117714_Utilising%20deep%20learning%20for%20classification_Scopus.pdf
http://irep.iium.edu.my/117714/
https://medic.upm.edu.my/upload/dokumen/2024123014111401_MJMHS_0662.pdf
