June 5, 2024, 4:49 a.m. | Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris, Gian Antonio Susto

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.02480v1 Announce Type: cross
Abstract: Deep Learning (DL) has made significant strides in various medical applications in recent years, achieving remarkable results. In the field of medical imaging, DL models can assist doctors in disease diagnosis by classifying pathologies in Chest X-ray images. However, training on new data to expand model capabilities and adapt to distribution shifts is a notable challenge these models face. Continual Learning (CL) has emerged as a solution to this challenge, enabling models to adapt to …

abstract applications arxiv capabilities continual cs.ai cs.cv data deep learning diagnosis disease disease diagnosis doctors eess.iv evolution expand fairness however images imaging medical medical imaging ray results training type x-ray

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