AIMC Topic: Neural Networks, Computer

Clear Filters Showing 17851 to 17860 of 31376 articles

The Budapest Amyloid Predictor and Its Applications.

Biomolecules
The amyloid state of proteins is widely studied with relevance to neurology, biochemistry, and biotechnology. In contrast with nearly amorphous aggregation, the amyloid state has a well-defined structure, consisting of parallel and antiparallel β-she...

Current applications of deep-learning in neuro-oncological MRI.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Magnetic Resonance Imaging (MRI) provides an essential contribution in the screening, detection, diagnosis, staging, treatment and follow-up in patients with a neurological neoplasm. Deep learning (DL), a subdomain of artificial intelligence...

Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks.

PLoS computational biology
The topology of protein folds can be specified by the inter-residue contact-maps and accurate contact-map prediction can help ab initio structure folding. We developed TripletRes to deduce protein contact-maps from discretized distance profiles by en...

Generalizability of machine learning models and empirical equations for the estimation of reference evapotranspiration from temperature in a semiarid region.

Anais da Academia Brasileira de Ciencias
The Penman-Monteith equation is recommended for the estimation of reference evapotranspiration (ETo). However, it requires meteorological data that are commonly unavailable. Thus, this study evaluates artificial neural network (ANN), multivariate ada...

Mask-Guided Attention Network and Occlusion-Sensitive Hard Example Mining for Occluded Pedestrian Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Pedestrian detection relying on deep convolution neural networks has made significant progress. Though promising results have been achieved on standard pedestrians, the performance on heavily occluded pedestrians remains far from satisfactory. The ma...

Optimization scheme of wind energy prediction based on artificial intelligence.

Environmental science and pollution research international
Wind energy, as one of the renewable energies with the most potential for development, has been widely concerned by many countries. However, due to the great volatility and uncertainty of natural wind, wind power also fluctuates, seriously affecting ...

Predicting Kováts Retention Indices Using Graph Neural Networks.

Journal of chromatography. A
The Kováts retention index is a dimensionless quantity that characterizes the rate at which a compound is processed through a gas chromatography column. This quantity is independent of many experimental variables and, as such, is considered a near-un...

Time-frequency time-space LSTM for robust classification of physiological signals.

Scientific reports
Automated analysis of physiological time series is utilized for many clinical applications in medicine and life sciences. Long short-term memory (LSTM) is a deep recurrent neural network architecture used for classification of time-series data. Here ...

Automated detection of critical findings in multi-parametric brain MRI using a system of 3D neural networks.

Scientific reports
With the rapid growth and increasing use of brain MRI, there is an interest in automated image classification to aid human interpretation and improve workflow. We aimed to train a deep convolutional neural network and assess its performance in identi...

Qualitative similarities and differences in visual object representations between brains and deep networks.

Nature communications
Deep neural networks have revolutionized computer vision, and their object representations across layers match coarsely with visual cortical areas in the brain. However, whether these representations exhibit qualitative patterns seen in human percept...