arXiv:2406.15958
공식 코드 · Papers with Code
Bone Fracture Classification using Transfer Learning
원문 초록
The manual examination of X-ray images for fractures is a time-consuming process that is prone to human error. In this work, we introduce a robust yet simple training loop for the classification of fractures, which significantly outperforms existing methods. Our method achieves superior performance in less than ten epochs and utilizes the latest dataset to deliver the best-performing model for this task. We emphasize the importance of training deep learning models responsibly and efficiently, as well as the critical role of selecting high-quality datasets.
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Lightweight Convolutional Neural Networks for Retinal Disease Classification
Multiview Contrastive Learning for Unsupervised Domain Adaptation in Brain–Computer Interfaces
Transfer Learning for Classification of Alzheimer's Disease Based on Genome Wide Data
Chest X-Ray Images Classification with CNN
DocXClassifier: High Performance Explainable Deep Network for Document Image Classification
ThanosNet: A Novel Trash Classification Method Using Metadata
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