Vision-based holistic scene understanding towards proactive human–robot collaboration
Recently human–robot collaboration (HRC) has emerged as a promising paradigm for mass
personalization in manufacturing owing to the potential to fully exploit the strength of human …
personalization in manufacturing owing to the potential to fully exploit the strength of human …
Multimodal Human–Robot Interaction for Human‐Centric Smart Manufacturing: A Survey
Human–robot interaction (HRI) has escalated in notability in recent years, and multimodal
communication and control strategies are necessitated to guarantee a secure, efficient, and …
communication and control strategies are necessitated to guarantee a secure, efficient, and …
[HTML][HTML] An adaptive reinforcement learning-based multimodal data fusion framework for human–robot confrontation gaming
Playing games between humans and robots have become a widespread human–robot
confrontation (HRC) application. Although many approaches were proposed to enhance the …
confrontation (HRC) application. Although many approaches were proposed to enhance the …
An improved localization of mobile robotic system based on AMCL algorithm
MA Chung, CW Lin - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
In the Mobile Robotics domain, the ability of robots to locate themselves is one of the most
important events. By locating, mobile robots can obtain information about the environment …
important events. By locating, mobile robots can obtain information about the environment …
Lightweight hybrid model based on MobileNet-v2 and Vision Transformer for human–robot interaction
X Cheng, F Lu, Y Liu - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Within convolutional neural networks, convolutional operations are good at extracting local
features, but have difficulty in capturing global representations. For Vision Transformer, multi …
features, but have difficulty in capturing global representations. For Vision Transformer, multi …
[PDF][PDF] Artificial Intelligence-Enabled Chatbots in Mental Health: A Systematic Review.
B Omarov, S Narynov… - Computers, Materials & …, 2023 - cdn.techscience.cn
Clinical applications of Artificial Intelligence (AI) for mental health care have experienced a
meteoric rise in the past few years. AI-enabled chatbot software and applications have been …
meteoric rise in the past few years. AI-enabled chatbot software and applications have been …
Sign Language Recognition With Self-Learning Fusion Model
Sign language recognition (SLR) is the task of recognizing human actions that represent the
language, which is not only helpful for deaf–mute people but also a means for human …
language, which is not only helpful for deaf–mute people but also a means for human …
Underwater accompanying robot based on ssdlite gesture recognition
T Liu, Y Zhu, K Wu, F Yuan - Applied Sciences, 2022 - mdpi.com
Underwater robots are often used in marine exploration and development to assist divers in
underwater tasks. However, the underwater robots on the market have some problems, such …
underwater tasks. However, the underwater robots on the market have some problems, such …
Millimeter wave gesture recognition using multi-feature fusion models in complex scenes
Z Hao, Z Sun, F Li, R Wang, J Peng - Scientific Reports, 2024 - nature.com
As a form of body language, the gesture plays an important role in smart homes, game
interactions, and sign language communication, etc. The gesture recognition methods have …
interactions, and sign language communication, etc. The gesture recognition methods have …
[HTML][HTML] Deep learning for hand tracking in Parkinson's disease video-based assessment: Current and future perspectives
Abstract Background: Parkinson's Disease (PD) demands early diagnosis and frequent
assessment of symptoms. In particular, analysing hand movements is pivotal to understand …
assessment of symptoms. In particular, analysing hand movements is pivotal to understand …