Intelligent agent and optimization‐based deep residual network to secure communication in UAV network
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22800
Abstract: Unmanned Aerial Vehicle (UAV) is adapted as a novel unit in upcoming wireless infrastructures wherein UAVs can play various roles in different applications. The UAV is utilized for navigating commands to attain surveillance. However, routing… read more here.
Keywords: network; deep residual; newly devised; uav network ... See more keywords
Deep residual learning for image steganalysis
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-4440-4
Abstract: Image steganalysis is to discriminate innocent images and those suspected images with hidden messages. This task is very challenging for modern adaptive steganography, since modifications due to message hiding are extremely small. Recent studies show… read more here.
Keywords: image steganalysis; residual learning; deep residual;
Image denoising via deep residual convolutional neural networks
Sign Up to like & getrecommendations! Published in 2021 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-019-01537-x
Abstract: Recently, convolutional neural network (CNN)-based methods have achieved impressive performance on image denoising. Notably, CNN with deeper and thinner structures is more flexible to extract the image details. However, direct stacking some existing networks is… read more here.
Keywords: deep residual; residual convolutional; denoising via; image ... See more keywords
Deep residual network for highly accelerated fMRI reconstruction using variable density spiral trajectory
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.02.070
Abstract: Abstract Compressed sensing has proved itself as a useful technique for accelerating time-consuming fMRI acquisition. However, its intrinsic iterative algorithm of solving optimization problems limits its practical usage. In addition, it may still suffer from… read more here.
Keywords: reconstruction; image; network; fmri reconstruction ... See more keywords
Smart crop disease monitoring system in IoT using optimization enabled deep residual network
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-85486-1
Abstract: Abstract The Internet of Things (IoT) has recently attracted substantial interest because of its diverse applications. In the agriculture sector, automated methods for detecting plant diseases offer numerous advantages over traditional methods. In the current… read more here.
Keywords: disease; deep residual; plant; network ... See more keywords
Accurate phase retrieval of complex 3D point spread functions with deep residual neural networks.
Sign Up to like & getrecommendations! Published in 2019 at "Applied physics letters"
DOI: 10.1063/1.5125252
Abstract: Phase retrieval, i.e., the reconstruction of phase information from intensity information, is a central problem in many optical systems. Imaging the emission from a point source such as a single molecule is one example. Here,… read more here.
Keywords: phase; point; point spread; phase retrieval ... See more keywords
Deep residual shrinkage network with multichannel VMD inputs for noise reduction of micro-thrust measurement
Sign Up to like & getrecommendations! Published in 2024 at "AIP Advances"
DOI: 10.1063/5.0200682
Abstract: Micro-newton thrusters are widely utilized in the field of astronautics. Typically, the precision of micro-newton thrust measurement fundamentally depends on the background noise level. In this research, we introduce the Multichannel Variational Mode Decomposition Input… read more here.
Keywords: noise reduction; deep residual; thrust measurement; shrinkage network ... See more keywords
Deep Residual Xception Network-Based Lung Cancer Detection Using CT Images
Sign Up to like & getrecommendations! Published in 2025 at "Cancer Investigation"
DOI: 10.1080/07357907.2025.2580957
Abstract: Abstract Lung cancer (LC) is one of the major causes of death worldwide. Early diagnosis helps to improve the patient survival outcome. The surgeon makes use of Computed Tomography (CT) for detecting LC using the… read more here.
Keywords: deep residual; lung; lung cancer; residual xception ... See more keywords
A multi-scale deep residual network-based guided wave imaging evaluation method for fatigue crack quantification
Sign Up to like & getrecommendations! Published in 2024 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/ad7e3e
Abstract: As a promising structural health monitoring technology, guided wave (GW) imaging is gaining increasing attention for crack monitoring of aircraft structures. However, actual fatigue crack propagation is a complex dynamically evolving process affected by various… read more here.
Keywords: deep residual; quantification; fatigue crack; crack ... See more keywords
Classification of multi-lead ECG with deep residual convolutional neural networks
Sign Up to like & getrecommendations! Published in 2022 at "Physiological Measurement"
DOI: 10.1088/1361-6579/ac7939
Abstract: Objective. Automatic electrocardiogram (ECG) interpretation based on deep learning methods is attracting increasing attention. In this study, we propose a novel method to accurately classify multi-lead ECGs using deep residual neural networks. Approach. ECG recordings… read more here.
Keywords: multi lead; neural networks; deep residual; convolutional neural ... See more keywords
Using deep Residual Networks to search for galaxy-Ly α emitter lens candidates based on spectroscopic selection
Sign Up to like & getrecommendations! Published in 2018 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/sty2708
Abstract: More than one hundred galaxy-scale strong gravitational lens systems have been found by searching for the emission lines coming from galaxies with redshifts higher than the lens galaxies. Based on this spectroscopic-selection method, we introduce… read more here.
Keywords: based spectroscopic; residual networks; networks search; spectroscopic selection ... See more keywords