📢 New relAI blog post!
AI models have recently revolutionized medical imaging by enabling automated analysis of complex radiological data. This includes tasks such as lesion detection, organ segmentation, and disease progression prediction. However, those models often overfit, learning patterns specific to the training dataset rather than acquiring generalizable visual concepts. In this blog post, relAI PhD student Aswathi introduces Random Convolutions, a method designed to enhance the generalization capabilities of AI models applied to medical images.
👉 https://zuseschoolrelai.de/blog/random-convolutions-a-simple-way-to-boost-generalization/
