Fan Zhang,Bangcheng Zhang
Fan Zhang
Introduction: In advanced robot systems, monitoring the health of key components such as bearings in the transmission system is crucial for achieving reliable autonomous operation. However, there are still challenges in a...
Xianmin Wang,Jing Li
Xianmin Wang
The evolution of trends and technology in wearable sensors used to detect falls in people with neurodegenerative diseases: a systematic review [0.03%]
Yuanzheng Chen,Tinghuai Huang,Zijie Lin et al.
Yuanzheng Chen et al.
Background: Neurodegenerative diseases (NDs) are a significant threat to human health. Numerous research demonstrated that patients with NDs might present with decreased balance, which is responsible for an increased risk...
SpikeAEC: a neuromodulation-based spiking controller for explore-exploit balancing in mobile robots [0.03%]
基于神经调制的脉冲控制器平衡移动机器人中探索与开发行为
Canyang Liu,Yichen Liu,Yongqi Zhou et al.
Canyang Liu et al.
Balancing exploration and exploitation remains a fundamental challenge in reliable mobile robot control, as conventional policies often converge on suboptimal behaviors. Inspired by the brain's division of labor for adaptive control, we pro...
Neurorobotics for automotive manufacturing industry in era of embodied intelligence: a mini review [0.03%]
具身智能时代的神经机器人在汽车制造业中的应用：迷你综述
Bangcheng Zhang,Qi Xia
Bangcheng Zhang
As automotive manufacturing advances toward the industrial 5.0 era, traditional rigid automation production models are transitioning toward the embodied intelligence paradigm. Confronted with mass customization, diverse products, and small-...
AMSA-Net: attention-based multi-scale feature aggregation network for single image dehazing [0.03%]
基于注意力的单图像去雾多尺度特征聚合网络 AMSA-Net
Shanqin Wang,Mengjun Miao,Miao Zhang
Shanqin Wang
Problem: Deep learning technology promotes the development of single-image dehazing. However, many existing methods fail to fully consider the haze density and its spatial distribution, which limits the improvement of deh...
Multimodal sequence dynamics and convergence optimization in dual-stream LSTM networks for complex physiological state estimation [0.03%]
基于双流LSTM网络的复杂生理状态估计的多模态序列动力学及收敛优化
Xiaoxiao Cao
Xiaoxiao Cao
Introduction: The integration of virtual simulation with intelligent modeling is crucial for advancing the scientization and personalization of volleyball physical training. This study aims to overcome the convergence ins...
Samer Attrah
Samer Attrah
Emotion estimation is a field that has been studied for a long time, and several approaches using machine learning models exist. This article presents BlendFER-Lite, an LSTM model that uses Blendshapes from the MediaPipe library to analyze ...
Transformer-based human-motion forecasting coupled with safe reinforcement learning for telepresence robot co-navigation [0.03%]
基于变压器的人体运动预测与安全增强学习相结合的远程呈现机器人共导航算法
Heba G Mohamed,Muhammad Nasir Khan,Fawad Naseer et al.
Heba G Mohamed et al.
Introduction: Telepresence robots (TPRs) must co-navigate with humans in constrained hospital environments, where safety depends on anticipating rather than merely reacting to human motion. Existing approaches rarely inte...
Motion feature extraction based on semi-supervised learning and long short-term memory network in digital dance [0.03%]
基于半监督学习和长短期记忆网络的数字舞蹈动作特征提取方法研究
Xue Yang,Hanmin Sun,Yin Lyu et al.
Xue Yang et al.
Digital-image technology has broadened the creative space of dance, yet accurately capturing the semantic correspondence between low-level motion data and high-level dance key-points remains challenging, especially when labeled data are sca...