This keynote presentation explores the employment of feature-based transfer learning through a series of medical imaging and bio-signals case studies. It introduces the concept of transfer learning and its benefits, focusing on the extraction and reuse of learned features from pre-trained models. The presentation showcases case studies in medical imaging as well as biologically driven signals such as EEG, amongst others. The keynote addresses challenges and considerations in transfer learning and emphasizes the importance of model selection, fine-tuning strategies, and evaluation metrics. Overall, it aims to inspire researchers and practitioners to leverage transfer learning to enhance performance and efficiency across diverse domains.
Period
20 Jan 2024
Event title
3rd International Conference on Big Data, Information and Computer Network