What are the emerging trends in the development of new fine-tuning techniques?

Deep learning practice is increasingly driven by powerful foundation models (FM), pre-trained at scale and then fine-tuned for specific tasks of interest. Oct 15, 2024 ... ... Fine-tuning deep learning architectures for early detection of oral cancer. In: 2nd International Symposium on Mathematical and ... Apr 18, 2022 ... In this article, we investigate the transfer learning of deep convolutional neural networks for the detection of maize leaf diseases. Dec 16, 2024 ... ... exploration of strongly correlated systems using NQS, mirroring the success of fine-tuning in machine learning and natural language processing. Chong Zhang 1, (张翀) Student Member, CCF,; Hong-Zhi Wang 1, (王宏志) Senior Member, IEEE, Member, CCF,; Hong-Wei Liu 1, , (刘宏伟) Member, CCF, ... 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 ... This FITML workshop aims to contribute to the recent radical paradigm shift for fine-tuning in modern machine learning, theoretically, computationally, and ... 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 ... 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. 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 ...