AIMC Topic: Neural Networks, Computer

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A method for real-time mechanical characterisation of microcapsules.

Biomechanics and modeling in mechanobiology
Characterising the mechanical properties of flowing microcapsules is important from both fundamental and applied points of view. In the present study, we develop a novel multilayer perceptron (MLP)-based machine learning (ML) approach, for real-time ...

Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks.

Journal of chemical theory and computation
Finding new enzyme variants with the desired substrate scope requires screening through a large number of potential variants. In a typical enzyme engineering workflow, it is possible to scan a few thousands of variants, and gather several candidates...

Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: application to surgical imaging.

International journal of computer assisted radiology and surgery
PURPOSE: Hyperspectral imaging has the potential to improve intraoperative decision making if tissue characterisation is performed in real-time and with high-resolution. Hyperspectral snapshot mosaic sensors offer a promising approach due to their fa...

DL-TODA: A Deep Learning Tool for Omics Data Analysis.

Biomolecules
Metagenomics is a technique for genome-wide profiling of microbiomes; this technique generates billions of DNA sequences called reads. Given the multiplication of metagenomic projects, computational tools are necessary to enable the efficient and acc...

EBi-LSTM: an enhanced bi-directional LSTM for time-series data classification by heuristic development of optimal feature integration in brain computer interface.

Computer methods in biomechanics and biomedical engineering
Generally, time series data is referred to as the sequential representation of data that observes from different applications. Therefore, such expertise can use Electroencephalography (EEG) signals to fetch data regarding brain neural activities in b...

Rapid quantification of royal jelly quality by mid-infrared spectroscopy coupled with backpropagation neural network.

Food chemistry
Royal jelly is rich in nutrients but its quality is greatly affected by storage conditions. To determine the quality of royal jelly accurately and quickly, a qualitative discrimination model was established based on the fusion of conventional paramet...

A quality-checked and physics-constrained deep learning method to estimate material basis images from single-kV contrast-enhanced chest CT scans.

Medical physics
BACKGROUND: Single-kV CT imaging is one of the primary imaging methods in radiology practices. However, it does not provide material basis images for some subtle lesion characterization tasks in clinical diagnosis.

Convolutional neural network-based automated maxillary alveolar bone segmentation on cone-beam computed tomography images.

Clinical oral implants research
OBJECTIVES: To develop and assess the performance of a novel artificial intelligence (AI)-driven convolutional neural network (CNN)-based tool for automated three-dimensional (3D) maxillary alveolar bone segmentation on cone-beam computed tomography ...

Human-Aware Collaborative Robots in the Wild: Coping with Uncertainty in Activity Recognition.

Sensors (Basel, Switzerland)
This study presents a novel approach to cope with the human behaviour uncertainty during Human-Robot Collaboration (HRC) in dynamic and unstructured environments, such as agriculture, forestry, and construction. These challenging tasks, which often r...