AIMC Topic: Neural Networks, Computer

Clear Filters Showing 11701 to 11710 of 31376 articles

Loosening Identification of Multi-Bolt Connections Based on Wavelet Transform and ResNet-50 Convolutional Neural Network.

Sensors (Basel, Switzerland)
A high-strength bolt connection is the key component of large-scale steel structures. Bolt loosening and preload loss during operation can reduce the load-carrying capacity, safety, and durability of the structures. In order to detect loosening damag...

Cofopose: Conditional 2D Pose Estimation with Transformers.

Sensors (Basel, Switzerland)
Human pose estimation has long been a fundamental problem in computer vision and artificial intelligence. Prominent among the 2D human pose estimation (HPE) methods are the regression-based approaches, which have been proven to achieve excellent resu...

Polyphonic Sound Event Detection Using Temporal-Frequency Attention and Feature Space Attention.

Sensors (Basel, Switzerland)
The complexity of polyphonic sounds imposes numerous challenges on their classification. Especially in real life, polyphonic sound events have discontinuity and unstable time-frequency variations. Traditional single acoustic features cannot character...

Enhanced detection of threat materials by dark-field x-ray imaging combined with deep neural networks.

Nature communications
X-ray imaging has been boosted by the introduction of phase-based methods. Detail visibility is enhanced in phase contrast images, and dark-field images are sensitive to inhomogeneities on a length scale below the system's spatial resolution. Here we...

Arrhythmia classification of 12-lead and reduced-lead electrocardiograms via recurrent networks, scattering, and phase harmonic correlation.

Physiological measurement
We describe an automatic classifier of arrhythmias based on 12-lead and reduced-lead electrocardiograms. Our classifier comprises four modules: scattering transform (ST), phase harmonic correlation (PHC), depthwise separable convolutions (DSC), and a...

Towards Exercise Radiomics: Deep Neural Network-Based Automatic Analysis of Thermal Images Captured During Exercise.

IEEE journal of biomedical and health informatics
Infrared thermography is increasingly applied in sports science due to promising observations regarding changes in skin's surface radiation temperature ( T) before, during, and after exercise. The common manual thermogram analysis limits an objective...

SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging.

IEEE journal of biomedical and health informatics
Federated learning is an emerging research paradigm for enabling collaboratively training deep learning models without sharing patient data. However, the data from different institutions are usually heterogeneous across institutions, which may reduce...

sEMG-Based Gesture Recognition Using Deep Learning From Noisy Labels.

IEEE journal of biomedical and health informatics
Gesture recognition for myoelectric prosthesis control utilizing sparse multichannel surface Electromyography (sEMG) is a challenging task, and from a Muscle-Computer Interface (MCI) standpoint, the performance is still far from optimal. However, the...

Application and Analysis of Improved Fuzzy Comprehensive Evaluation Method in Goodwill Evaluation and Intangible Asset Management.

Computational intelligence and neuroscience
In order to improve the effect of goodwill evaluation and intangible asset management, this paper combines the improved fuzzy comprehensive evaluation method to construct an intelligent algorithm. In order to consider the many influencing factors of ...

Lite-3DCNN Combined with Attention Mechanism for Complex Human Movement Recognition.

Computational intelligence and neuroscience
Three-dimensional convolutional network (3DCNN) is an essential field of motion recognition research. The research work of this paper optimizes the traditional three-dimensional convolution network, introduces the self-attention mechanism, and propos...