AIMC Topic: Neural Networks, Computer

Clear Filters Showing 15511 to 15520 of 31376 articles

Convolutional neural network performance compared to radiologists in detecting intracranial hemorrhage from brain computed tomography: A systematic review and meta-analysis.

European journal of radiology
PURPOSE: To compare the diagnostic accuracy of convolutional neural networks (CNN) with radiologists as the reference standard in the diagnosis of intracranial hemorrhages (ICH) with non contrast computed tomography of the cerebrum (NCTC).

Trends in the application of deep learning networks in medical image analysis: Evolution between 2012 and 2020.

European journal of radiology
PURPOSE: To evaluate the general rules and future trajectories of deep learning (DL) networks in medical image analysis through bibliometric and hot spot analysis of original articles published between 2012 and 2020.

Self-Supervised Denoising Image Filter Based on Recursive Deep Neural Network Structure.

Sensors (Basel, Switzerland)
The purpose of this paper is to propose a novel noise removal method based on deep neural networks that can remove various types of noise without paired noisy and clean data. Because this type of filter generally has relatively poor performance, the ...

Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures.

Sensors (Basel, Switzerland)
Human stress is intricately linked with mental processes such as decision making. Public protection practitioners, including Law Enforcement Agents (LEAs), are forced to make difficult decisions during high-pressure operations, under strenuous circum...

Underwater Target Signal Classification Using the Hybrid Routing Neural Network.

Sensors (Basel, Switzerland)
In signal analysis and processing, underwater target recognition (UTR) is one of the most important technologies. Simply and quickly identify target types using conventional methods in underwater acoustic conditions is quite a challenging task. The p...

Visual design intuition: predicting dynamic properties of beams from raw cross-section images.

Journal of the Royal Society, Interface
In this work we aim to mimic the human ability to acquire the intuition to estimate the performance of a design from visual inspection and experience alone. We study the ability of convolutional neural networks to predict static and dynamic propertie...

Crowd density estimation using deep learning for Hajj pilgrimage video analytics.

F1000Research
BACKGROUND: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security...

Deep Learning Technology in Pathological Image Analysis of Breast Tissue.

Journal of healthcare engineering
To explore the application value of the multilevel pyramid convolutional neural network (MPCNN) model based on convolutional neural network (CNN) in breast histopathology image analysis, in this study, based on CNN algorithm and softmax classifier (S...

Analysis of Influencing Factors on Hospitalization Expenses of Patients with Breast Malignant Tumor Undergoing Surgery: Based on the Neural Network and Support Vector Machine.

Journal of healthcare engineering
OBJECTIVE: Analyze the influencing factors of hospitalization expenses of breast cancer patients in a tertiary hospital in Chengdu and provide a basis and suggestion for controlling the unreasonable increase of medical expenses.

Supervised Learning Algorithm for Multilayer Spiking Neural Networks with Long-Term Memory Spike Response Model.

Computational intelligence and neuroscience
As a new brain-inspired computational model of artificial neural networks, spiking neural networks transmit and process information via precisely timed spike trains. Constructing efficient learning methods is a significant research field in spiking n...