AIMC Topic: Pattern Recognition, Automated

Clear Filters Showing 101 to 110 of 1689 articles

Adapting Action Recognition Neural Networks for Automated Infantile Spasm Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Infantile spasms are a severe epileptic syndrome characterized by short muscular contractions lasting from 0.5 to 2 seconds. They are often misdiagnosed due to their atypical presentation, and treatment is frequently delayed, leading to stagnation or...

Pattern recognition using spiking antiferromagnetic neurons.

Scientific reports
Spintronic devices offer a promising avenue for the development of nanoscale, energy-efficient artificial neurons for neuromorphic computing. It has previously been shown that with antiferromagnetic (AFM) oscillators, ultra-fast spiking artificial ne...

Hand gesture recognition using sEMG signals with a multi-stream time-varying feature enhancement approach.

Scientific reports
Hand gesture recognition based on sparse multichannel surface electromyography (sEMG) still poses a significant challenge to deployment as a muscle-computer interface. Many researchers have been working to develop an sEMG-based hand gesture recogniti...

DMGNet: Depth mask guiding network for RGB-D salient object detection.

Neural networks : the official journal of the International Neural Network Society
Though depth images can provide supplementary spatial structural cues for salient object detection (SOD) task, inappropriate utilization of depth features may introduce noisy or misleading features, which may greatly destroy SOD performance. To addre...

Machine Learning-Based Gesture Recognition Glove: Design and Implementation.

Sensors (Basel, Switzerland)
In the evolving field of human-computer interaction (HCI), gesture recognition has emerged as a critical focus, with smart gloves equipped with sensors playing one of the most important roles. Despite the significance of dynamic gesture recognition, ...

Touchformer: A Transformer-Based Two-Tower Architecture for Tactile Temporal Signal Classification.

IEEE transactions on haptics
Haptic temporal signal recognition plays an important supporting role in robot perception. This paper investigates how to improve classification performance on multiple types of haptic temporal signal datasets using a Transformer model structure. By ...

Improving Human Activity Recognition With Wearable Sensors Through BEE: Leveraging Early Exit and Gradient Boosting.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Early-exiting has recently provided an ideal solution for accelerating activity inference by attaching internal classifiers to deep neural networks. It allows easy activity samples to be predicted at shallower layers, without executing deeper layers,...

Bio-inspired deep neural local acuity and focus learning for visual image recognition.

Neural networks : the official journal of the International Neural Network Society
In the field of computer vision and image recognition, enabling the computer to discern target features while filtering out irrelevant ones poses a challenge. Drawing insights from studies in biological vision, we find that there is a local visual ac...

Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The objective of this work is to develop a novel myoelectric pattern recognition (MPR) method to mitigate the concurrent interference of electrode shift and loosening, thereby improving the practicality of MPR-based gestural interfaces towards intell...

Object and spatial discrimination makes weakly supervised local feature better.

Neural networks : the official journal of the International Neural Network Society
Local feature extraction plays a crucial role in numerous critical visual tasks. However, there remains room for improvement in both descriptors and keypoints, particularly regarding the discriminative power of descriptors and the localization precis...