What are the considerations when fine tuning models for safety-critical applications?

Jul 2, 2024 ... This study aims to enhance precision of a popular commercial DLAS product in rectal cancer radiotherapy by localized fine-tuning. We present GOODFIT, one of the first optimizers that has been specifically designed to operate on converged models that need to be incrementally fine-tuned ... Deep neural networks have been highly successful across a multitude of domains, from computer vision [1, 2] and natural language processing [3, 4], to game ... Jan 10, 2025 ... Specialization: Fine-tuning lets you customize a model to excel at a specific task. It's like tailoring a versatile suit to fit an individual. We investigate generalization properties of fine-tuning to understand the problem of overfitting, which often happens in practice. Jul 17, 2023 ... As a machine learning practitioner, you might often find yourself in a situation where you're fine-tuning a pre-trained model for your specific ... Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning. IEEE Trans Med Imaging. 2018 Jul;37(7):1562-1573. doi: 10.1109 ... Feb 13, 2025 ... Fine-tuning is a form of transfer learning where the pre-trained model is adjusted to better fit the new data. There are several steps involved ... Use the Export Training Data For Deep Learning tool to prepare training data for fine-tuning the model. Browse to Tools under the Analysis tab. Tools icon. Oct 3, 2016 ... A Comprehensive guide to Fine-tuning Deep Learning Models in Keras (Part I) · 1. The common practice is to truncate the last layer (softmax ...