AFP-SRC: identification of antifreeze proteins using sparse representation classifier
Sign Up to like & getrecommendations! Published in 2022 at "Neural Computing and Applications"
DOI: 10.1007/s00521-021-06558-7
Abstract: Species living in the extreme cold environment fight against the harsh conditions using antifreeze proteins (AFPs), which manipulate the freezing mechanism of water in more than one way. This amazing nature of AFPs turns out… read more here.
Keywords: src identification; using sparse; afp src; antifreeze proteins ... See more keywords
Short-Range Clutter Suppression for Airborne Radar Using Sparse Recovery and Orthogonal Projection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.3023780
Abstract: For nonside-looking airborne radar (NSLAR), the range-dependent near-range clutter degrades the performance of space–time adaptive processing (STAP), especially in the high-pulse-repetition-frequency mode. To solve this problem, a novel algorithm using sparse recovery (SR) and orthogonal… read more here.
Keywords: short range; using sparse; range; airborne radar ... See more keywords
Drone Detection Using Sparse Lidar Measurements
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3145498
Abstract: Unmanned aerial vehicles (UAV) have been serving people, fulfilling various roles in research, industry and military, not to exclude personal entertainment. They have also been in use more often for malicious purposes, such as annoying… read more here.
Keywords: using sparse; detection; detection using; sparse lidar ... See more keywords
Wideband Cyclostationary Signal Processing Using Sparse Subsets of Narrowband Subchannels
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2018.2790971
Abstract: The problem of signal detection and modulation recognition is addressed in both the blind and nonblind contexts. Many relevant modulation recognition algorithms have been created over the past three decades. The essential engineering tradeoff that… read more here.
Keywords: using sparse; wideband cyclostationary; sparse subsets; cyclostationary signal ... See more keywords
Reduction of Power System Dynamic Models Using Sparse Representations
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Power Systems"
DOI: 10.1109/tpwrs.2017.2648979
Abstract: This paper proposes a model reduction technique that simplifies the dynamic equations of complex power networks, using sparse representations of the system matrices. Instead of removing components from the state vector, elements from the system… read more here.
Keywords: reduction; system; sparse representations; using sparse ... See more keywords
Adaptive Detection of Diverse Forest Disturbances Using Sparse Landsat Time Series
Sign Up to like & getrecommendations! Published in 2025 at "Polish Journal of Environmental Studies"
DOI: 10.15244/pjoes/202593
Abstract: Most change detection algorithms are designed to detect specific forest disturbances, which may not effectively capture diverse events. These algorithms typically model seasonal changes using dense observations to reduce phenological noise, making them unsuitable for… read more here.
Keywords: detection; forest disturbances; sparse landsat; using sparse ... See more keywords
Single Image Dehazing Using Sparse Contextual Representation
Sign Up to like & getrecommendations! Published in 2021 at "Atmosphere"
DOI: 10.3390/atmos12101266
Abstract: In this paper, we propose a novel method to remove haze from a single hazy input image based on the sparse representation. In our method, the sparse representation is proposed to be used as a… read more here.
Keywords: image; dehazing using; using sparse; image dehazing ... See more keywords