AIMC Topic: Neural Networks, Computer

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A deep learning approach for automated scoring of the Rey-Osterrieth complex figure.

eLife
Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across the globe to assess the degree of non-verbal visu...

LRMAHpan: a novel tool for multi-allelic HLA presentation prediction using Resnet-based and LSTM-based neural networks.

Frontiers in immunology
INTRODUCTION: The identification of peptides eluted from HLA complexes by mass spectrometry (MS) can provide critical data for deep learning models of antigen presentation prediction and promote neoantigen vaccine design. A major challenge remains in...

CC-TransXNet: a hybrid CNN-transformer network for automatic segmentation of optic cup and optic disk from fundus images.

Medical & biological engineering & computing
Accurate segmentation of the optic disk (OD) and optic cup (OC) regions of the optic nerve head is a critical step in glaucoma diagnosis. Existing architectures based on convolutional neural networks (CNNs) still suffer from insufficient global infor...

TENet: Targetness entanglement incorporating with multi-scale pooling and mutually-guided fusion for RGB-E object tracking.

Neural networks : the official journal of the International Neural Network Society
There is currently strong interest in improving visual object tracking by augmenting the RGB modality with the output of a visual event camera that is particularly informative about the scene motion. However, existing approaches perform event feature...

Incorporating label uncertainty during the training of convolutional neural networks improves performance for the discrimination between certain and inconclusive cases in dopamine transporter SPECT.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep convolutional neural networks (CNN) hold promise for assisting the interpretation of dopamine transporter (DAT)-SPECT. For improved communication of uncertainty to the user it is crucial to reliably discriminate certain from inconclusiv...

Static pinning synchronization control of self-triggered coupling dynamical networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, a new static pinning intermittent control based on resource awareness triggering is proposed. A multi-layer control technique is used to synchronize the coupled neural network. First, a hierarchical network structure including pinned a...

Research on Risk Prediction of Condiments Based on Gray Correlation Analysis - Deep Neural Networks.

Journal of food protection
Food safety is directly related to the health of the public, and the safety of condiments is also of great significance. In this study, a risk assessment model for condiments based on gray correlation analysis was established by using publicly availa...

Bonevoyage: Navigating the depths of osteoporosis detection with a dual-core ensemble of cascaded ShuffleNet and neural networks.

Journal of X-ray science and technology
BACKGROUND: Osteoporosis (OP) is a condition that significantly decreases bone density and strength, often remaining undetected until the occurrence of a fracture. Timely identification of OP is essential for preventing fractures, reducing morbidity,...

CLHGNNMDA: Hypergraph Neural Network Model Enhanced by Contrastive Learning for miRNA-Disease Association Prediction.

Journal of computational biology : a journal of computational molecular cell biology
Numerous biological experiments have demonstrated that microRNA (miRNA) is involved in gene regulation within cells, and mutations and abnormal expression of miRNA can cause a myriad of intricate diseases. Forecasting the association between miRNA an...

Taming Prolonged Ionic Drift-Diffusion Dynamics for Brain-Inspired Computation.

Advanced materials (Deerfield Beach, Fla.)
Recent advances in neural network-based computing have enabled human-like information processing in areas such as image classification and voice recognition. However, many neural networks run on conventional computers that operate at GHz clock freque...