AIMC Topic: Neural Networks, Computer

Clear Filters Showing 23361 to 23370 of 31376 articles

An unsupervised convolutional neural network-based algorithm for deformable image registration.

Physics in medicine and biology
The purpose of the work is to develop a deep unsupervised learning strategy for cone-beam CT (CBCT) to CT deformable image registration (DIR). This technique uses a deep convolutional inverse graphics network (DCIGN) based DIR algorithm implemented o...

Cascaded atrous convolution and spatial pyramid pooling for more accurate tumor target segmentation for rectal cancer radiotherapy.

Physics in medicine and biology
Convolutional neural networks (CNNs) have become the state-of-the-art method for medical segmentation. However, repeated pooling and striding operations reduce the feature resolution, causing loss of detailed information. Additionally, tumors of diff...

Abstract concept learning in a simple neural network inspired by the insect brain.

PLoS computational biology
The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly h...

Nondestructive determination of freshness indicators for tilapia fillets stored at various temperatures by hyperspectral imaging coupled with RBF neural networks.

Food chemistry
This study develops a reliable radial basis function neural networks (RBFNNs) to estimate freshness for tilapia fillets stored under non-isothermal conditions by using optimal wavelengths from hyperspectral imaging (HSI). The results show that, for t...

Comparison of multi-linear regression, particle swarm optimization artificial neural networks and genetic programming in the development of mini-tablets.

International journal of pharmaceutics
In the present study, the preparation of pharmaceutical mini-tablets was attempted in the framework of Quality by Design (QbD) context, by comparing traditionally used multi-linear regression (MLR), with artificially-intelligence based regression tec...

Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review.

Neural computation
Analysis and forecasting of sequential data, key problems in various domains of engineering and science, have attracted the attention of many researchers from different communities. When predicting the future probability of events using time series, ...

Cross-Entropy Pruning for Compressing Convolutional Neural Networks.

Neural computation
The success of CNNs is accompanied by deep models and heavy storage costs. For compressing CNNs, we propose an efficient and robust pruning approach, cross-entropy pruning (CEP). Given a trained CNN model, connections were divided into groups in a gr...

Robust Closed-Loop Control of a Cursor in a Person with Tetraplegia using Gaussian Process Regression.

Neural computation
Intracortical brain computer interfaces can enable individuals with paralysis to control external devices through voluntarily modulated brain activity. Decoding quality has been previously shown to degrade with signal nonstationarities-specifically, ...

Comparative Study for Optimization of Pharmaceutical Self-Emulsifying Pre-concentrate by Design of Experiment and Artificial Neural Network.

AAPS PharmSciTech
The present investigation aimed to optimize the critical parameters affecting the globule size of self-emulsifying drug delivery system. Based on preliminary screening, three critical parameters, viz., amount of oil, surfactant, and co-surfactant wer...

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction ...