Results 11 to 20 of about 243,195 (329)
Semi‐supervised classification of fundus images combined with CNN and GCN
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose Diabetic retinopathy (DR) is one of the most serious complications of diabetes, which is a kind of fundus lesion with specific changes. Early diagnosis of DR can effectively reduce the visual damage caused by DR. Due to the variety and different morphology of DR lesions, automatic classification of fundus images in mass screening can ...
Sixu Duan +8 more
wiley +1 more source
Fully Learnable Model for Task-Driven Image Compressed Sensing
Sensors, 2021 This study primarily investigates image sensing at low sampling rates with convolutional neural networks (CNN) for specific applications. To improve the image acquisition efficiency in energy-limited systems, this study, inspired by compressed sensing ...
Bowen Zheng +3 more
doaj +1 more source
An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher
Entropy, 2022 In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption.
Xiaomeng Song +3 more
doaj +1 more source
Compressed Sensing in Astronomy [PDF]
IEEE Journal of Selected Topics in Signal Processing, 2008 Recent advances in signal processing have focused on the use of sparse representations in various applications. A new field of interest based on sparsity has recently emerged: compressed sensing. This theory is a new sampling framework that provides an alternative to the well-known Shannon sampling theory.
Jérôme Bobin +2 more
openaire +4 more sources
Distributed Compressed Hyperspectral Sensing Imaging Based on Spectral Unmixing
Sensors, 2020 The huge volume of hyperspectral imagery demands enormous computational resources, storage memory, and bandwidth between the sensor and the ground stations.
Zhongliang Wang, Hua Xiao
doaj +1 more source
Kinetic Compressive Sensing [PDF]
2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2017 5 pages, 6 figures, Submitted to the Conference Record of "IEEE Nuclear Science Symposium and Medical Imaging Conference (IEEE NSS-MIC) 2017"
Scipioni Michele +6 more
openaire +4 more sources
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley +1 more source
Sensors, 2020 With the widespread application of wireless sensor networks, large-scale systems with high sampling rates are becoming more and more common. The amount of original data generated by the wireless sensor network is very large, and transmitting all the ...
Youtian Qie, Chuangbo Hao, Ping Song
doaj +1 more source
Sensors, 2023 High-definition images covering entire large-scene construction sites are increasingly used for monitoring management. However, the transmission of high-definition images is a huge challenge for construction sites with harsh network conditions and scarce
Tuocheng Zeng +4 more
doaj +1 more source
Advanced Engineering Materials, EarlyView., 2023 The study presents the mechanical and in situ sensing performance of digital light processing‐enabled 2D lattice nanocomposites under monotonic tensile and repeated cyclic loading, and provides guidelines for the design of architectures suitable for strain sensors and smart lightweight structures.
Omar Waqas Saadi +3 more
wiley +1 more source