AIMC Topic: Algorithms

Clear Filters Showing 26121 to 26130 of 28713 articles

Neural networks for classification of cervical vertebrae maturation: a systematic review.

The Angle orthodontist
OBJECTIVE: To assess the accuracy of identification and/or classification of the stage of cervical vertebrae maturity on lateral cephalograms by neural networks as compared with the ground truth determined by human observers.

Improved pig behavior analysis by optimizing window sizes for individual behaviors on acceleration and angular velocity data.

Journal of animal science
This paper presents the application of machine learning algorithms to identify pigs' behaviors from data collected using the wireless sensor nodes mounted on pigs. The sensor node attached to a pig's back senses the acceleration and angular velocity ...

dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: In multi-cohort machine learning studies, it is critical to differentiate between effects that are reproducible across cohorts and those that are cohort-specific. Multi-task learning (MTL) is a machine learning approach that facilitates t...

[Cascaded multi-level medical image registration method based on transformer].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In deep learning-based image registration, the deformable region with complex anatomical structures is an important factor affecting the accuracy of network registration. However, it is difficult for existing methods to pay attention to complex anato...

VDE-Net: a two-stage deep learning method for phase unwrapping.

Optics express
Phase unwrapping is a critical step to obtaining a continuous phase distribution in optical phase measurements and coherent imaging techniques. Traditional phase-unwrapping methods are generally low performance due to significant noise or undersampli...

Fourier ptychographic microscopy with untrained deep neural network priors.

Optics express
We propose a physics-assisted deep neural network scheme in Fourier ptychographic microscopy (FPM) using untrained deep neural network priors (FPMUP) to achieve a high-resolution image reconstruction from multiple low-resolution images. Unlike the tr...

Intelligent design of the chiral metasurfaces for flexible targets: combining a deep neural network with a policy proximal optimization algorithm.

Optics express
Recently, deep reinforcement learning (DRL) for metasurface design has received increased attention for its excellent decision-making ability in complex problems. However, time-consuming numerical simulation has hindered the adoption of DRL-based des...

Cardiac CTA image quality of adaptive statistical iterative reconstruction-V versus deep learning reconstruction "TrueFidelity" in children with congenital heart disease.

Medicine
BACKGROUND: Several recent studies have reported that deep learning reconstruction "TrueFidelity" (TF) improves computed tomography (CT) image quality. However, no study has compared adaptive statistical repeated reconstruction (ASIR-V) using TF in p...

Disease classification for whole-blood DNA methylation: Meta-analysis, missing values imputation, and XAI.

GigaScience
BACKGROUND: DNA methylation has a significant effect on gene expression and can be associated with various diseases. Meta-analysis of available DNA methylation datasets requires development of a specific workflow for joint data processing.