Results 61 to 70 of about 1,813,028 (298)
Multiscale Union Regions Adaptive Sparse Representation for Hyperspectral Image Classification
Remote Sensing, 2017 Sparse Representation has been widely applied to classification of hyperspectral images (HSIs). Besides spectral information, the spatial context in HSIs also plays an important role in the classification.
Fei Tong +3 more
doaj +1 more source
Remote Sensing, 2020 In recent years, with the development of compressed sensing theory, sparse representation methods have been concerned by many researchers. Sparse representation can approximate the original image information with less space storage. Sparse representation
Xiaobin Zhao +4 more
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Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Convolutional sparse coding network for sparse seismic time-frequency representation
Artificial Intelligence in GeosciencesSeismic time-frequency (TF) transforms are essential tools in reservoir interpretation and signal processing, particularly for characterizing frequency variations in non-stationary seismic data.
Qiansheng Wei +5 more
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Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Loose L1/2 regularised sparse representation for face recognition
IET Computer Vision, 2015 Sparse representation (or sparse coding) has been applied to deal with frontal face recognition. Two representative methods are the sparse representation‐based classification (SRC) and the collaborative representation‐based classification (CRC), in which
Dexing Zhong +3 more
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Parametric Sparse Representation and Its Applications to Radar Sensing
Leida xuebao, 2016 Sparse signal processing has been utilized to the area of radar sensing. Due to the presence of unknown factors such as the motion of the targets of interest and the error of the radar trajectory, a predesigned dictionary cannot provide the optimally ...
Li Gang, Xia Xiang-Gen
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Kernel difference maximisation-based sparse representation for more accurate face recognition
The Journal of Engineering, 2020 Most methods for sparse representation are designed to be used in the original space. However, their performance is not always satisfactory especially when training samples are limited.
Lian Wu +4 more
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Sparse Matrix Representation for Web Opinions [PDF]
, 2012 Due to the advancement of Web 2.0 technologies, a large volume of Web opinions is available on social media sites such as Web forums and Weblogs. These technologies provide a platform for Internet users around the world to communicate with each other and
Dileep kumar B R +1 more
core
Clustering before training large datasets - Case study: K-SVD [PDF]
, 2012 Training and using overcomplete dictionaries has been the subject of many developments in the area of signal processing and sparse representations. The main idea is to train a dictionary that is able to achieve good sparse representations of the items ...
Rusu, Cristian
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