AIMC Topic: Neural Networks, Computer

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Contour-constrained branch U-Net for accurate left ventricular segmentation in echocardiography.

Medical & biological engineering & computing
Using echocardiography to assess the left ventricular function is one of the most crucial cardiac examinations in clinical diagnosis, and LV segmentation plays a particularly vital role in medical image processing as many important clinical diagnosti...

Near-field millimeter-wave and visible image fusion via transfer learning.

Neural networks : the official journal of the International Neural Network Society
To facilitate penetrating-imaging oriented applications such as nondestructive internal defect detection and localization under obstructed environment, a novel pixel-level information fusion strategy for mmWave and visible images is proposed. More co...

DyGraphformer: Transformer combining dynamic spatio-temporal graph network for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society
Transformer-based models demonstrate tremendous potential for Multivariate Time Series (MTS) forecasting due to their ability to capture long-term temporal dependencies by using the self-attention mechanism. However, effectively modeling the spatial ...

Optimization and correction of breast dynamic optical imaging projection data based on deep learning.

Computational biology and chemistry
Breast cancer poses a significant health threat to women, necessitating advancements in diagnostic technologies. Breast dynamic optical imaging (DOI) technology, recognized for its non-invasive and radiation-free properties, is extensively utilized f...

Explainable artificial intelligence and domain adaptation for predicting HIV infection with graph neural networks.

Annals of medicine
OBJECTIVE: Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and performing domain adaptation to evaluate model transferability across different datasets.

Neural parameter calibration and uncertainty quantification for epidemic forecasting.

PloS one
The recent COVID-19 pandemic has thrown the importance of accurately forecasting contagion dynamics and learning infection parameters into sharp focus. At the same time, effective policy-making requires knowledge of the uncertainty on such prediction...

Automatic Hardy and Clapham's classification of hallux sesamoid position on foot radiographs using deep neural network.

Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons
BACKGROUND: There is currently no deep neural network (DNN) capable of automatically classifying tibial sesamoid position (TSP) on foot radiographs.

Tipping prediction of a class of large-scale radial-ring neural networks.

Neural networks : the official journal of the International Neural Network Society
Understanding the emergence and evolution of collective dynamics in large-scale neural networks remains a complex challenge. This paper seeks to address this gap by applying dynamical systems theory, with a particular focus on tipping mechanisms. Fir...

Adaptive indefinite kernels in hyperbolic spaces.

Neural networks : the official journal of the International Neural Network Society
Learning embeddings in hyperbolic space has gained increasing interest in the community, due to its property of negative curvature, as a way of encoding data hierarchy. Recent works investigate the improvement of the representation power of hyperboli...

Deep plug-and-play MRI reconstruction based on multiple complementary priors.

Magnetic resonance imaging
Magnetic resonance imaging (MRI) is widely used in clinical diagnosis as a safe, non-invasive, high-resolution medical imaging technology, but long scanning time has been a major challenge for this technology. The undersampling reconstruction method ...