Results 61 to 70 of about 6,849,681 (296)
Augmented Reality based 3D Human Hands Tracking from Monocular True Images Using Convolutional Neural Network [PDF]
, 2023 Precise modeling of hand tracking from monocular moving camera calibration parameters using semantic cues is an active area of research concern for the researchers due to lack of accuracy and computational overheads.
Saif, A F M Saifuddin +1 more
core +1 more source
Fully automated quantitative cephalometry using convolutional neural networks [PDF]
Journal of Medical Imaging, 2017 Quantitative cephalometry plays an essential role in clinical diagnosis, treatment, and surgery. Development of fully automated techniques for these procedures is important to enable consistently accurate computerized analyses. We study the application of deep convolutional neural networks (CNNs) for fully automated quantitative cephalometry for the ...
Sercan Ö, Arık +2 more
openaire +2 more sources
Artificial Neural Networks and Evolutionary Computation in Remote Sensing [PDF]
, 2021 Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images.
core +1 more source
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Arthritis Care &Research, Accepted Article.Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
Image Aesthetics Assessment Using Fully Convolutional Neural Networks [PDF]
, 2018 This paper presents a new method for assessing the aesthetic quality of images. Based on the findings of previous works on this topic, we propose a method that addresses the shortcomings of existing ones, by: (a) Making possible to feed higher-resolution images in the network, by introducing a fully convolutional neural network as the classifier.
Apostolidis, Konstantinos +1 more
openaire +3 more sources
3D convolutional neural network for schizophrenia detection using as EEG-based functional brain network [PDF]
Schizophrenia (ScZ) is a chronic mental disorder affecting the function of the brain, which causes emotional, social, and cognitive problems.
Wen, Peng +3 more
core +1 more source
Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis
Arthritis Care &Research, EarlyView.Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling +4 more
wiley +1 more source
A Convolutional Neural Network Fully Implemented on FPGA for Embedded Platforms [PDF]
2017 New Generation of CAS (NGCAS), 2017 Convolutional Neural Networks (CNNs) allow fast and precise image recognition. Nowadays this capability is highly requested in the embedded system domain for video processing applications such as video surveillance and homeland security. Moreover, with the increasing requirement of portable and ubiquitous processing, power consumption is a key issue to
BETTONI, MARCO +4 more
openaire +3 more sources
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source