AIMC Topic: Neural Networks, Computer

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EDeepSSP: Explainable deep neural networks for exact splice sites prediction.

Journal of bioinformatics and computational biology
Splice site prediction is crucial for understanding underlying gene regulation, gene function for better genome annotation. Many computational methods exist for recognizing the splice sites. Although most of the methods achieve a competent performanc...

Recognition of Crop Diseases Based on Depthwise Separable Convolution in Edge Computing.

Sensors (Basel, Switzerland)
The original pattern recognition and classification of crop diseases needs to collect a large amount of data in the field and send them next to a computer server through the network for recognition and classification. This method usually takes a long...

ECG Biometrics Using Deep Learning and Relative Score Threshold Classification.

Sensors (Basel, Switzerland)
The field of biometrics is a pattern recognition problem, where the individual traits are coded, registered, and compared with other database records. Due to the difficulties in reproducing Electrocardiograms (ECG), their usage has been emerging in t...

Research of Epidemic Big Data Based on Improved Deep Convolutional Neural Network.

Computational and mathematical methods in medicine
In recent years, with the acceleration of the aging process and the aggravation of life pressure, the proportion of chronic epidemics has gradually increased. A large amount of medical data will be generated during the hospitalization of diabetics. I...

Deep learning using a biophysical model for robust and accelerated reconstruction of quantitative, artifact-free and denoised images.

Magnetic resonance in medicine
PURPOSE: To introduce a novel deep learning method for Robust and Accelerated Reconstruction (RoAR) of quantitative and B0-inhomogeneity-corrected maps from multi-gradient recalled echo (mGRE) MRI data.

Intermittent boundary stabilization of stochastic reaction-diffusion Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
Cohen-Grossberg neural networks (CGNNs) play an important role in many applications and the stabilization of this system has been well studied. This study considers the exponential stabilization for stochastic reaction-diffusion Cohen-Grossberg neura...

Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.

Medical image analysis
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the crucial step in fighting COVID-19 is the ability to detect the infected p...

Automatic skin lesion classification based on mid-level feature learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dermoscopic images are widely used for melanoma detection. Many existing works based on traditional classification methods and deep learning models have been proposed for automatic skin lesion analysis. The traditional classification methods use hand...

Multi-site household waste generation forecasting using a deep learning approach.

Waste management (New York, N.Y.)
Forecasting household waste generation using traditional methods is particularly challenging due to its high variability and uncertainty. Unlike studies that forecast waste generation at municipal or country levels, household data can present rapid s...

Capsule networks as recurrent models of grouping and segmentation.

PLoS computational biology
Classically, visual processing is described as a cascade of local feedforward computations. Feedforward Convolutional Neural Networks (ffCNNs) have shown how powerful such models can be. However, using visual crowding as a well-controlled challenge, ...