IEEE transactions on neural networks and learning systems
Feb 28, 2025
Human activity recognition (HAR) is a popular research field in computer vision that has already been widely studied. However, it is still an active research field since it plays an important role in many current and emerging real-world intelligent s...
This study proposes a novel gesture recognition system based on LoRa technology, integrating advanced signal preprocessing, adaptive segmentation algorithms, and an improved SS-ResNet50 deep learning model. Through the combination of residual learnin...
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...
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...
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...
Neural networks : the official journal of the International Neural Network Society
Feb 10, 2025
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...
IEEE transactions on neural networks and learning systems
Feb 6, 2025
Spiking neural networks (SNNs) mimic their biological counterparts more closely than their predecessors and are considered the third generation of artificial neural networks. It has been proven that networks of spiking neurons have a higher computati...
IEEE transactions on neural networks and learning systems
Feb 6, 2025
Transfer learning is one of the popular methods to solve the problem of insufficient data in subject-specific electroencephalogram (EEG) recognition tasks. However, most existing approaches ignore the difference between subjects and transfer the same...
IEEE transactions on neural networks and learning systems
Feb 6, 2025
This article proposes a semi-supervised contrastive capsule transformer method with feature-based knowledge distillation (KD) that simplifies the existing semisupervised learning (SSL) techniques for wearable human activity recognition (HAR), called ...
Biomedizinische Technik. Biomedical engineering
Jan 29, 2025
OBJECTIVES: In recent years, significant progress has been made in the research of gesture recognition using surface electromyography (sEMG) signals based on machine learning and deep learning techniques. The main motivation for sEMG gesture recognit...
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