AIMC Topic: Neural Networks, Computer

Clear Filters Showing 11241 to 11250 of 31376 articles

Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network.

Acta dermato-venereologica
Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with...

Generation and Research of Online English Course Learning Evaluation Model Based on Genetic Algorithm Improved Neural Set Network.

Computational intelligence and neuroscience
The rationality and timeliness of the comprehensive results of English course learning quality are increasingly important in the process of modern education. There are some problems in the scientific evaluation of English course learning quality and ...

Predictive Analysis of Diabetes-Risk with Class Imbalance.

Computational intelligence and neuroscience
Diabetes type 2 (T2DM) is a common chronic disease, increasingly leading to many complications and affecting vital organs. Hyperglycemia is the main characteristic caused by insufficient insulin secretion and poses a serious risk to human health. The...

CAW: A Remote-Sensing Scene Classification Network Aided by Local Window Attention.

Computational intelligence and neuroscience
Remote-sensing image scene data contain a large number of scene images with different scales. Traditional scene classification algorithms based on convolutional neural networks are difficult to extract complex spatial distribution and texture informa...

Evaluation of Regional Economic Innovation Ability Based on Neural Network.

Computational intelligence and neuroscience
In order to further improve regional economic innovation capability and governance level and solve the problems of lack of attention to evaluation indicators in traditional evaluation methods of regional economic innovation capability and easy to be ...

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

BioMed research international
PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by i...

A novel 3D lumbar vertebrae location and segmentation method based on the fusion envelope of 2D hybrid visual projection images.

Computers in biology and medicine
In recent years, fast and precise lumbar vertebrae segmentation technology have been one of the important topics in practical medical diagnosis and assisted medical surgery scenarios. However, most of the existing vertebral segmentation methods are b...

Lag H synchronization in coupled reaction-diffusion neural networks with multiple state or derivative couplings.

Neural networks : the official journal of the International Neural Network Society
This paper mainly attempts to discuss lag H synchronization in multiple state or derivative coupled reaction-diffusion neural networks without and with parameter uncertainties. Firstly, we respectively propose two types of reaction-diffusion neural n...

Shared subspace-based radial basis function neural network for identifying ncRNAs subcellular localization.

Neural networks : the official journal of the International Neural Network Society
Non-coding RNAs (ncRNAs) play an important role in revealing the mechanism of human disease for anti-tumor and anti-virus substances. Detecting subcellular locations of ncRNAs is a necessary way to study ncRNA. Traditional biochemical methods are tim...

Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat?

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the "black box" model. Fundamental limitations remain, however, that impede the pace of understanding ...