Results 41 to 50 of about 5,528,069 (258)
Lithosphere, 2021 Average pore pressure in oil formation is an important parameter to measure energy in the formation and the capacity of injection–production. In past studies, average pore pressure mainly depends on pressure build-up test results, which have a high cost ...
Chaoyang Hu +4 more
doaj +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
Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification
IEEE Access, 2021 A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design ...
Kaisheng Liao +4 more
doaj +1 more source
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
, 2020 This paper explores the value of weak-ties in classifying academic literature with the use of graph convolutional neural networks. Our experiments look at the results of treating weak-ties as if they were strong-ties to determine if that assumption ...
Gita Sukthankar +2 more
core +1 more source
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 +3 more
wiley +1 more source
Research onconvolutional neural network for reservoir parameter prediction
Tongxin xuebao, 2016 As the branch of artificial intelligence,artificial neural network solved many difficult practical problems in pattern recognition and classification prediction field successfully.However,they cannot learn the feature from networks.In recent years,deep ...
You-xiang DUAN, Gen-tian LI, Qi-feng SUN
doaj +2 more sources
Research on road extraction of remote sensing image based on convolutional neural network
EURASIP Journal on Image and Video Processing, 2019 Road is an important kind of basic geographic information. Road information extraction plays an important role in traffic management, urban planning, automatic vehicle navigation, and emergency management.
Yuantao Jiang
doaj +1 more source
SMT Assembly Inspection Using Dual-Stream Convolutional Networks and Two Solder Regions
Applied Sciences, 2020 The automated optical inspection of a surface mount technology line inspects a printed circuit board for quality assurance, and subsequently classifies the chip assembly defects.
Young-Gyu Kim, Tae-Hyoung Park
doaj +1 more source
An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression
Sensors, 2023 Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual ...
Guoliang Luo +6 more
doaj +1 more source