Results 31 to 40 of about 136,882 (282)
Leaf Classification for Crop Pests and Diseases in the Compressed Domain
Sensors, 2022 Crop pests and diseases have been the main cause of reduced food production and have seriously affected food security. Therefore, it is very urgent and important to solve the pest problem efficiently and accurately.
Jing Hua, Tuan Zhu, Jizhong Liu
doaj +1 more source
On Known-Plaintext Attacks to a Compressed Sensing-based Encryption: A Quantitative Analysis [PDF]
, 2015 Despite the linearity of its encoding, compressed sensing may be used to provide a limited form of data protection when random encoding matrices are used to produce sets of low-dimensional measurements (ciphertexts).
Cambareri, Valerio +4 more
core +2 more sources
Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems
International Journal of Antennas and Propagation, 2015 Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum sensing has considerable technical challenges, especially in wideband systems where higher sampling rates are required which increases the complexity and ...
Taha A. Khalaf +2 more
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Sensors, 2021 Infrared images of power equipment play an important role in power equipment status monitoring and fault identification. Aiming to resolve the problems of low resolution and insufficient clarity in the application of infrared images, we propose a blind ...
Yan Wang +3 more
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Recovery of binary sparse signals from compressed linear measurements via polynomial optimization [PDF]
, 2019 The recovery of signals with finite-valued components from few linear measurements is a problem with widespread applications and interesting mathematical characteristics.
Abuabiah, Mohammad, Fosson, Sophie M.
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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 +3 more sources
Perceptual Compressive Sensing [PDF]
, 2018 Accepted by The First Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2018). This is a pre-print version (not final version)
Jiang Du 0011 +3 more
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Improved Algorithm for Compressed Sensing Channel Estimation Based on DFT Path Searching [PDF]
Jisuanji gongcheng, 2022 Signals in Orthogonal Frequency Division Multiplexing(OFDM) systems are influenced by environmental decline in wireless channels and delay, causing Inter Symbol Interference(ISI).Accurate estimation of Channel State Information(CSI) is an effective ...
FANG Haitao, LI Mingqi, BIAN Xin
doaj +1 more source
Randomness and isometries in echo state networks and compressed sensing
, 2018 Although largely different concepts, echo state networks and compressed sensing models both rely on collections of random weights; as the reservoir dynamics for echo state networks, and the sensing coefficients in compressed sensing.
Prater-Bennette, Ashley
core +1 more source
Mixed Operators in Compressed Sensing [PDF]
, 2010 Applications of compressed sensing motivate the possibility of using different operators to encode and decode a signal of interest. Since it is clear that the operators cannot be too different, we can view the discrepancy between the two matrices as a ...
Herman, Matthew A., Needell, Deanna
core +3 more sources