9 papers
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…
Development of a Compliant Gripper for Safe Robot-Assisted Trouser Dressing-Undressing
Jayant Unde, Takumi Inden, Yuki Wakayama +4
In recent years, many countries, including Japan, have rapidly aging populations, making the preservation of seniors' quality of life a significant concern. For elderly people with…
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…
Affordance-Based Disambiguation of Surgical Instructions for Collaborative Robot-Assisted Surgery
Ana Davila, Jacinto Colan, Yasuhisa Hasegawa
Effective human-robot collaboration in surgery is affected by the inherent ambiguity of verbal communication. This paper presents a framework for a robotic surgical assistant that…
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…
Assessing the Value of Visual Input: A Benchmark of Multimodal Large Language Models for Robotic Path Planning
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
Large Language Models (LLMs) show potential for enhancing robotic path planning. This paper assesses visual input's utility for multimodal LLMs in such tasks via a comprehensive be…