AIMC Topic: Neural Networks, Computer

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Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.

Scientific reports
An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT) dataset....

Predicting Social Events with Multimodal Fusion of Spatial and Temporal Dynamic Graph Representations.

Big data
Big data has been satisfactorily used to solve social issues in several parts of the word. Social event prediction is related to social stability and sustainable development. However, current research rarely takes into account the dynamic connections...

Explainability and causability for artificial intelligence-supported medical image analysis in the context of the European In Vitro Diagnostic Regulation.

New biotechnology
Artificial Intelligence (AI) for the biomedical domain is gaining significant interest and holds considerable potential for the future of healthcare, particularly also in the context of in vitro diagnostics. The European In Vitro Diagnostic Medical D...

Prediction of MODIS land surface temperature using new hybrid models based on spatial interpolation techniques and deep learning models.

Environmental science and pollution research international
Land surface temperature (LST) prediction is of great importance for climate change, ecology, environmental and industrial studies. These studies require accurate LST map predictions considering both spatial and temporal dynamics. In this study, mult...

Replacing pooling functions in Convolutional Neural Networks by linear combinations of increasing functions.

Neural networks : the official journal of the International Neural Network Society
Traditionally, Convolutional Neural Networks make use of the maximum or arithmetic mean in order to reduce the features extracted by convolutional layers in a downsampling process known as pooling. However, there is no strong argument to settle upon ...

ExSpliNet: An interpretable and expressive spline-based neural network.

Neural networks : the official journal of the International Neural Network Society
In this paper we present ExSpliNet, an interpretable and expressive neural network model. The model combines ideas of Kolmogorov neural networks, ensembles of probabilistic trees, and multivariate B-spline representations. We give a probabilistic int...

Multi-input adaptive neural network for automatic detection of cervical vertebral landmarks on X-rays.

Computers in biology and medicine
Cervical vertebral landmark detection is a significant pre-task for vertebral relative motion parameter measurement, which is helpful for doctors to diagnose cervical spine diseases. Accurate cervical vertebral landmark detection could provide reliab...

A Feed-Forward Neural Network for Increasing the Hopfield-Network Storage Capacity.

International journal of neural systems
In the hippocampal dentate gyrus (DG), pattern separation mainly depends on the concepts of 'expansion recoding', meaning random mixing of different DG input channels. However, recent advances in neurophysiology have challenged the theory of pattern ...

Exploring Complex Reaction Networks Using Neural Network-Based Molecular Dynamics Simulation.

The journal of physical chemistry letters
molecular dynamics (AIMD) is an established method for revealing the reactive dynamics of complex systems. However, the high computational cost of AIMD restricts the explorable length and time scales. Here, we develop a fundamentally different appro...

End-to-End Residual Network for Light Field Reconstruction on Raw Images and View Image Stacks.

Sensors (Basel, Switzerland)
Light field (LF) technology has become a focus of great interest (due to its use in many applications), especially since the introduction of the consumer LF camera, which facilitated the acquisition of dense LF images. Obtaining densely sampled LF im...