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Pattern Recognition, Automated

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A Graph Neural Network Model for Real-Time Gesture Recognition Based on sEMG Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
For seemless control of advanced hand prostheses and augmented reality, accurate and immediate hand gestures recognition is essential. Surface electromyography (sEMG) signals obtained from the forearm are commonly employed for this purpose. In this p...

[Gesture accuracy recognition based on grayscale image of surface electromyogram signal and multi-view convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
This study aims to address the limitations in gesture recognition caused by the susceptibility of temporal and frequency domain feature extraction from surface electromyography signals, as well as the low recognition rates of conventional classifiers...

Epileptic seizure detection in EEG signals via an enhanced hybrid CNN with an integrated attention mechanism.

Mathematical biosciences and engineering : MBE
Epileptic seizures, a prevalent neurological condition, necessitate precise and prompt identification for optimal care. Nevertheless, the intricate characteristics of electroencephalography (EEG) signals, noise, and the want for real-time analysis re...

DT-Transformer: A Text-Tactile Fusion Network for Object Recognition.

IEEE transactions on haptics
Humans rely on multiple senses to understand their surroundings, and so do robots. Current research in haptic object classification focuses on visual-haptic methods, but faces limitations in performance and dataset size. Unlike images, text does not ...

Object Recognition Using Shape and Texture Tactile Information: A Fusion Network Based on Data Augmentation and Attention Mechanism.

IEEE transactions on haptics
Currently, most tactile-based object recognition algorithms focus on single shape or texture recognition. However, these single attribute-based recognition methods perform poorly when dealing with objects with similar shape or texture characteristics...

Convolutional neural network for gesture recognition human-computer interaction system design.

PloS one
Gesture interaction applications have garnered significant attention from researchers in the field of human-computer interaction due to their inherent convenience and intuitiveness. Addressing the challenge posed by the insufficient feature extractio...

The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.

PloS one
This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. Firstly, the data collected in this study come fr...

A Novel Improvement of Feature Selection for Dynamic Hand Gesture Identification Based on Double Machine Learning.

Sensors (Basel, Switzerland)
Causal machine learning is an approach that combines causal inference and machine learning to understand and utilize causal relationships in data. In current research and applications, traditional machine learning and deep learning models always focu...

Intervening on few-shot object detection based on the front-door criterion.

Neural networks : the official journal of the International Neural Network Society
Most few-shot object detection methods aim to utilize the learned generalizable knowledge from base categories to identify instances of novel categories. The fundamental assumption of these approaches is that the model can acquire sufficient transfer...

sEMG-Based Gesture Recognition via Multi-Feature Fusion Network.

IEEE journal of biomedical and health informatics
The sparse surface electromyography-based gesture recognition suffers from the problems of feature information not richness and poor generalization to small sample data. Therefore, a multi-feature fusion network (MFF-Net) model is proposed in this pa...