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
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
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
Specific Emitter Identification Based on Deep Residual Networks
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2913759
Abstract: Specific emitter identification (SEI) enables the discrimination of individual radio emitters with the external features carried by the received waveforms. This identification technique has been widely adopted in military and civil applications. However, many previous… read more here.
Keywords: emitter identification; specific emitter; deep residual; hilbert spectrum ... See more keywords
Deep Residual Learning Using Data Augmentation for Median Filtering Forensics of Digital Images
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2923000
Abstract: This paper addresses the median filtering forensics for a lossy compressed image with low resolution, which is essential for the identification of fake images and fake videos. A deep residual model with training data augmentation… read more here.
Keywords: deep residual; median filtering; filtering forensics; image ... See more keywords
Underwater Image Enhancement With a Deep Residual Framework
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2928976
Abstract: Owing to refraction, absorption, and scattering of light by suspended particles in water, raw underwater images have low contrast, blurred details, and color distortion. These characteristics can significantly interfere with visual tasks, such as segmentation… read more here.
Keywords: loss; deep residual; image enhancement; underwater image ... See more keywords
Identifying Malicious Software Using Deep Residual Long-Short Term Memory
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2951751
Abstract: The use of smartphone applications based on the Android OS platform is rapidly growing among smartphone users. However, malicious apps for Android are being developed to perform attacks, such as destroying operating systems, stealing confidential… read more here.
Keywords: term memory; long short; deep residual; short term ... See more keywords