What types of pre-trained models are commonly used for fine tuning?

A fine-tuning deep learning framework to palliate data distribution shift effects in rotary machine fault detection. Nima Rezazadeh, Perfetto Donato, Mario ... We investigate generalization properties of fine-tuning to understand the problem of overfitting, which often happens in practice. Oct 8, 2024 ... Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery. Feb 28, 2025 ... For the learning rate during fine-tuning, we often use a value up to 10 times smaller than usual. As a result, our model will try to adapt ... Nov 21, 2017 ... Fine-tuning is a way of applying or utilizing transfer learning. Specifically, fine-tuning is a process that takes a model that has already been ... One of the major challenges currently facing researchers in applying deep learning (DL) models to medical image analysis is the limited amount of annotated ... Oct 15, 2024 ... ... Fine-tuning deep learning architectures for early detection of oral cancer. In: 2nd International Symposium on Mathematical and ... 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 ... Transfer learning, which aims to transfer knowledge from source tasks to a target task, is an effective solution to this problem. Fine-tuning is a popular ... Aug 24, 2016 ... Here in Part 2, I describe Deep Convolutional Neural Networks (DCNNs) and how Transfer learning and Fine-tuning helps better the training process for domain ...