AIMC Topic: Neural Networks, Computer

Clear Filters Showing 28491 to 28500 of 31376 articles

A global gridded municipal water withdrawal estimation method using aggregated data and artificial neural network.

Water science and technology : a journal of the International Association on Water Pollution Research
Municipal water withdrawal (MWW) information is of great significance for water supply planning, including water supply pipeline networks planning, optimization and management. Currently most MWW data are reported as spatially aggregated over large-a...

3D-equivariant graph neural networks for protein model quality assessment.

Bioinformatics (Oxford, England)
MOTIVATION: Quality assessment (QA) of predicted protein tertiary structure models plays an important role in ranking and using them. With the recent development of deep learning end-to-end protein structure prediction techniques for generating highl...

Classification of EEG signals related to real and imagery knee movements using deep learning for brain computer interfaces.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Non-invasive Brain-Computer Interface (BCI) uses an electroencephalogram (EEG) to obtain information on brain neural activity. Because EEG can be contaminated by various artifacts during the collection process, it has primarily evolved in...

Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks.

Cognitive science
Convolutional neural networks (CNNs) are increasingly widely used in psychology and neuroscience to predict how human minds and brains respond to visual images. Typically, CNNs represent these images using thousands of features that are learned throu...

Image restoration for blurry optical images caused by photon diffusion with deep learning.

Journal of the Optical Society of America. A, Optics, image science, and vision
Optical macroscopic imaging techniques have shown great significance in the investigations of biomedical issues by revealing structural or functional information of living bodies through the detection of visible or near-infrared light derived from di...

[Automatic anatomical site recognition of laryngoscopic images using convolutional neural network].

Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery
To explore the automatic recognition and classification of 20 anatomical sites in laryngoscopy by an artificial intelligence(AI) quality control system using convolutional neural network(CNN). Laryngoscopic image data archived from laryngoscopy exam...

DFinder: a novel end-to-end graph embedding-based method to identify drug-food interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Drug-food interactions (DFIs) occur when some constituents of food affect the bioaccessibility or efficacy of the drug by involving in drug pharmacodynamic and/or pharmacokinetic processes. Many computational methods have achieved remarka...

Coded aperture compressive temporal imaging using complementary codes and untrained neural networks for high-quality reconstruction.

Optics letters
The coded aperture compressive temporal imaging (CACTI) modality is capable of capturing dynamic scenes with only a single-shot of a 2D detector. In this Letter, we present a specifically designed CACTI system to boost the reconstruction quality. Our...

VdistCox: Vertically distributed Cox proportional hazards model with hyperparameter optimization.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Vertically partitioned data is distributed data in which information about a patient is distributed across multiple sites. In this study, we propose a novel algorithm (referred to as VdistCox) for the Cox proportional hazards model (Cox model), which...