A5101790411- Hand Gesture Recognition Systems
- Muscle activation and electromyography studies
- EEG and Brain-Computer Interfaces
- Robotic Path Planning Algorithms
- Robot Manipulation and Learning
- Robotic Mechanisms and Dynamics
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Industrial Vision Systems and Defect Detection
- Gait Recognition and Analysis
- Robotics and Sensor-Based Localization
- Advanced Neural Network Applications
- Manufacturing Process and Optimization
- Soft Robotics and Applications
- Advanced Manufacturing and Logistics Optimization
- Image Processing Techniques and Applications
- Advanced Sensor and Control Systems
- Optical measurement and interference techniques
- E-commerce and Technology Innovations
- Advanced Algorithms and Applications
- Industrial Technology and Control Systems
- Brain Tumor Detection and Classification
- Tactile and Sensory Interactions
- Advanced Image and Video Retrieval Techniques
- Digital Transformation in Industry
Wuhan University of Science and Technology
2017-2025
Shanghai First People's Hospital
2024
China Three Gorges University
2023
University of Portsmouth
2023
University of California, San Diego
2006-2021
Xi'an Technological University
2016
Dongfang Electric Corporation (China)
2012
Hebei University of Technology
2007-2011
Dalian Polytechnic University
2010-2011
Chengdu University of Information Technology
2008
Human computer interaction plays an increasingly important role in our life. People need more intelligent, concise and efficient human-computer interaction. It is of great significance to optimize the process by using appropriate calculation methods. In order eliminate interference data thumb recognition based on sEMG signal interaction, simplify processing, improve working efficiency general equipment signal. gesture signals generated thumb, a method redundant electrode determination...
Abstract In the production and construction of industry, safety accidents caused by unsafe behaviors staff often occur. a complex site scene, due to improper operations personnel, huge risks will be buried in entire process. The use deep learning algorithms replace manual monitoring regulations is powerful guarantee for sticking line production. First, improved YOLO v3 algorithm used output predicted anchor box target object, then pixel feature statistics are performed on box, weight...
Mobile robots have an important role in material handling manufacturing and can be used for a variety of automated tasks. The accuracy the robot’s moving trajectory has become key issue affecting its work efficiency. This paper presents method optimizing mobile robot based on digital twin robot. is created by Unity, trained virtual environment applied to physical space. simulation training provides schemes actual movement Based data returned robot, preset dynamically adjusted, which turn...
With the manipulator performs fixed-point tasks, it becomes adversely affected by external disturbances, parameter variations, and random noise. Therefore, is essential to improve robust accuracy of controller. In this article, a self-tuning particle swarm optimization (PSO) fuzzy PID positioning controller designed based on control. The quantization scaling factors in algorithm are optimized PSO order achieve high robustness manipulator. First all, mathematical model developed, designed. A...
In order to solve the problems of poor image quality, loss detail information and excessive brightness enhancement during in low light environment, we propose a low-light algorithm based on improved multi-scale Retinex Artificial Bee Colony (ABC) optimization this paper. First all, makes two copies original image, afterwards, irradiation component is obtained by used structure extraction from texture via relative total variation for first combines it with obtain reflection which are...
The continuous development of deep learning improves target detection technology day by day. current research focuses on improving the accuracy technology, resulting in model being too large. number parameters and speed are very important for practical application embedded systems. This article proposed a real-time method based lightweight convolutional neural network to reduce improve speed. In this article, depthwise separable residual module is constructed combining convolution...
In order to realize the force control, when prosthetic hand grasps object, forearm electromyography signal is collected by multi-channel surface (sEMG) acquisition system. The grasping information of human recorded six-dimensional sensor. root mean square (RMS) steady state selected, which an effective feature. gene expression programming algorithm (GEP) and BP neural network are used construct prediction model predict force. accuracy GEP discussed under different power levels modes....
The brain is the largest and most complex structure in central nervous system. It dominates all activities body, lesions human body are also reflected signal. In this paper, image method used to assist signal detect lesion. Due particularity of medical images, there no common segmentation for any image, objective standard judge whether effective. Medical technology still a bottleneck restricting development application other related technologies processing. Based on above reasons, paper...
Gesture recognition technology is widely used in the flexible and precise control of manipulators assisted medical field. Our MResLSTM algorithm can effectively perform dynamic gesture recognition. The result surface EMG signal decoding applied to controller, which improve fluency artificial hand control. Much current research using sEMG has focused on static gestures. In addition, accuracy depends extraction selection features. However, Static cannot meet requirements natural human-computer...
Summary For the problem of surface electromyography (sEMG) gesture recognition, considering fact that traditional machine learning model is susceptible to sEMG feature extraction method, it difficult distinguish subtle differences between similar gestures. The NinaPro DB1 dataset used as research object, and image Convolutional Neural Network (CNN) are combined recognize 52 movements. CNN effectively solves limitations in combines 1‐dim convolution kernel extract deep abstract features...
Summary With the continuous development of sensor technology, acquisition cost RGB‐D images is getting lower and lower, gesture recognition based on depth Red‐Green‐Blue (RGB) has gradually become a research direction in field pattern recognition. However, most current processing methods for are relatively simple, ignoring relationship influence between its two modes, unable to make full use correlation factors different modes. In view above problems, this paper optimizes effect information...
With the diversity of manipulator grasping methods and complexity unstructured environment, planning target object is very complicated. However, external factor for primarily shape object. Therefore, it great significance to establish a system based on analysis. This paper proposes method determining posture analysis force closure. The irregular or complex objects are reduced combination some basic shapes. 3D data points split into blocks each part fitted sphere, cylinder rectangle by...
In order to improve the operation performance and environmental adaptability of manipulator, it is essential control position force manipulator simultaneously. This paper proposed a hybrid method auto-dynamic bit based on realize flexible grasping in unknown environment. The constraint conditions types force/bit are analyzed firstly, dynamic model when contacting with environment established. Then, an improved controller conventional fuzzy-PID strategy introduced by combining estimation...
The analysis of robot inverse kinematic solutions is the basis control and path planning, great importance for research. Due to limitations analytical geometric methods, intelligent algorithms are more advantageous because they can obtain approximate directly from robot's positive equations, saving a large number computational steps. Particle Swarm Algorithm (PSO), as one algorithms, widely used due its simple principle excellent performance. In this paper, we propose an improved particle...
Gesture recognition is one of the important ways human‐computer interaction, which mainly detected by visual technology. The temporal and spatial features are extracted convolution video containing gesture. However, compared with calculation a single image, multiframe image dynamic gestures has more computation, complex feature extraction, network parameters, affects efficiency real‐time performance model. To solve above problems, gesture model based on CBAM‐C3D proposed. Key frame...