Why is fine tuning often more efficient than training from scratch?

Nov 7, 2023 ... When fine-tuning, it's common to adjust the deeper layers of the model while keeping the initial layers fixed. The rationale is that the initial ... Jul 2, 2024 ... This study aims to enhance precision of a popular commercial DLAS product in rectal cancer radiotherapy by localized fine-tuning. This tutorial will walk through the process of transfer learning from a pre-trained network and a minimal approach to hyperparamater tuning. 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 ... Jun 18, 2017 ... Can anyone share his code for using finetuning alexnet please? I am very new to all pytorch and deep learning and it would really help. One of the major challenges currently facing researchers in applying deep learning (DL) models to medical image analysis is the limited amount of annotated ... Aug 16, 2024 ... The very last classification layer (on "top", as most diagrams of machine learning models go from bottom to top) is not very useful. Instead ... Apr 18, 2022 ... In this article, we investigate the transfer learning of deep convolutional neural networks for the detection of maize leaf diseases. Jan 31, 2025 ... Transforming a foundation LLM into a solution that meets an application's needs requires a process called fine-tuning. Mar 16, 2020 ... This paper presents segmentation of multiple organ regions from non-contrast CT volume based on deep learning. Also, we report usefulness of fine-tuning.