4 papers · 1 filter
Bio-inspired fine-tuning for selective transfer learning in image classification
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Deep learning has significantly advanced image analysis across diverse domains but often depends on large, annotated datasets for success. Transfer learning addresses this challeng…
Adaptive transfer learning for surgical tool presence detection in laparoscopic videos through gradual freezing fine-tuning
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Minimally invasive surgery can benefit significantly from automated surgical tool detection, enabling advanced analysis and assistance. However, the limited availability of annotat…
Transfer learning optimization based on evolutionary selective fine tuning
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
Deep learning has shown substantial progress in image analysis. However, the computational demands of large, fully trained models remain a consideration. Transfer learning offers a…
Comparison of fine-tuning strategies for transfer learning in medical image classification
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
In the context of medical imaging and machine learning, one of the most pressing challenges is the effective adaptation of pre-trained models to specialized medical contexts. Despi…