AIMC Topic: Neural Networks, Computer

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Multi-dimensional feature recognition model based on capsule network for ubiquitination site prediction.

PeerJ
Ubiquitination is an important post-translational modification of proteins that regulates many cellular activities. Traditional experimental methods for identification are costly and time-consuming, so many researchers have proposed computational met...

Convolutional ProteinUnetLM competitive with long short-term memory-based protein secondary structure predictors.

Proteins
The protein secondary structure (SS) prediction plays an important role in the characterization of general protein structure and function. In recent years, a new generation of algorithms for SS prediction based on embeddings from protein language mod...

An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data.

Magnetic resonance in medicine
PURPOSE: To implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data.

A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Among the most frequently diagnosed cancers in developing countries, esophageal squamous cell carcinoma (ESCC) ranks among the top six causes of death. It would be beneficial if a rapid, accurate, and automatic ESCC diagnostic method could be develop...

Deep neural network automated segmentation of cellular structures in volume electron microscopy.

The Journal of cell biology
Volume electron microscopy is an important imaging modality in contemporary cell biology. Identification of intracellular structures is a laborious process limiting the effective use of this potentially powerful tool. We resolved this bottleneck with...

A CNN-RNN unified framework for intrapartum cardiotocograph classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prenatal fetal monitoring, which can monitor the growth and health of the fetus, is very vital for pregnant women before delivery. During pregnancy, it is crucial to judge whether the fetus is abnormal, which helps obstetric...

Synchronization of hybrid switching diffusions delayed networks via stochastic event-triggered control.

Neural networks : the official journal of the International Neural Network Society
In this paper, the synchronization problem of stochastic complex networks with time delays and hybrid switching diffusions (SCNTH) is concerned based on event-triggered control. Therein, a new class of event-triggered function is proposed for the con...

Deformable Protein Shape Classification Based on Deep Learning, and the Fractional Fokker-Planck and Kähler-Dirac Equations.

IEEE transactions on pattern analysis and machine intelligence
The classification of deformable protein shapes, based solely on their macromolecular surfaces, is a challenging problem in protein-protein interaction prediction and protein design. Shape classification is made difficult by the fact that proteins ar...

Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction.

IEEE transactions on pattern analysis and machine intelligence
Predicting human motion from historical pose sequence is crucial for a machine to succeed in intelligent interactions with humans. One aspect that has been obviated so far, is the fact that how we represent the skeletal pose has a critical impact on ...

Computer State Evaluation Using Adaptive Neuro-Fuzzy Inference Systems.

Sensors (Basel, Switzerland)
Several crucial system design and deployment decisions, including workload management, sizing, capacity planning, and dynamic rule generation in dynamic systems such as computers, depend on predictive analysis of resource consumption. An analysis of ...