Zobrazeno 1 - 10
of 2 075
pro vyhledávání: '"Sehee An"'
Publikováno v:
Applied Sciences, Vol 14, Iss 2, p 672 (2024)
This study conducted a survey to identify the best ergonomic operation method, in-vehicle location, and the effects of their combination on electronic gearshifts. A total of 15 different design alternatives were derived through combinations of three
Externí odkaz:
https://doaj.org/article/b4e69b86015f4ff984ba51d1dcbd3b98
Publikováno v:
Applied Sciences, Vol 12, Iss 12, p 5823 (2022)
The accident rate due to human errors in industrial fields has been consistently high over the past few decades, and noise has been emerging as one of the main causes of human errors. In recent years, auditory pre-stimulation has been considered as a
Externí odkaz:
https://doaj.org/article/307ed10fd3f148a9971bee97708263b4
Improving the accessibility of psychotherapy with the aid of Large Language Models (LLMs) is garnering a significant attention in recent years. Recognizing cognitive distortions from the interviewee's utterances can be an essential part of psychother
Externí odkaz:
http://arxiv.org/abs/2403.14255
Addressing the challenge of limited labeled data in clinical settings, particularly in the prediction of fatty liver disease, this study explores the potential of graph representation learning within a semi-supervised learning framework. Leveraging g
Externí odkaz:
http://arxiv.org/abs/2403.02786
Autor:
Balasubramaniam, Sasitharan, Somathilaka, Samitha, Sun, Sehee, Ratwatte, Adrian, Pierobon, Massimiliano
Artificial Intelligence (AI) and Machine Learning (ML) are weaving their way into the fabric of society, where they are playing a crucial role in numerous facets of our lives. As we witness the increased deployment of AI and ML in various types of de
Externí odkaz:
http://arxiv.org/abs/2212.11910
The common research goal of self-supervised learning is to extract a general representation which an arbitrary downstream task would benefit from. In this work, we investigate music audio representation learned from different contrastive self-supervi
Externí odkaz:
http://arxiv.org/abs/2207.04471
Autor:
Park, Sehee, Perumalsamy, Haribalan, Kim, Ji Eun, Kim, Hye Young, Jun, Dae Won, Yoon, Tae Hyun
Publikováno v:
In Biomedicine & Pharmacotherapy September 2024 178
Publikováno v:
In Journal of Science: Advanced Materials and Devices September 2024 9(3)
Publikováno v:
In Nano Energy January 2025 133
Understanding the relation between anatomy andgait is key to successful predictive gait simulation. Inthis paper, we present Generative GaitNet, which isa novel network architecture based on deep reinforce-ment learning for controlling a comprehensiv
Externí odkaz:
http://arxiv.org/abs/2201.12044