Adaptive Neighborhood Regularization(ANR)Low-Rank and Sparse Representation(LRSR)method has gained popularity in Hyperspectral Image(HSI)processing.However,existing LRSR models rarely exploited spectral-spatial classification of HSI.In this paper,we proposed a novel Low-Rank and Sparse Representation with ...
Infrared small target detection is still one of the key techniques in the infrared search and track systems. We proposed a robust and efficient detection method by exploiting low-rank and sparse representation. We extend traditional low-rank and sparse representation to temporal domain. Initially, we...
A novel method for anomaly detection in hyperspectral images (HSIs) is proposed based on low-rank and sparse representation. The proposed method is based on the separation of the background and the anomalies in the observed data. Since each pixel in the background can be approximately represente...
研究者提出了一种新颖的算法,利用这种表示方法对高光谱图像进行分析,并识别出与背景不同的异常区域。实验结果表明,这种方法在处理高维数据和复杂背景下具有很好的性能,为高光谱图像中的异常检测问题提供了一种有效且可靠的解决方案。Anomaly-Detection-in-Hyperspectral-Images-Based-on-Low-Rank-and-Sparse-Representation...
BLSE has two steps, i.e., block-diagonal constrained low-rank and sparse representation (BLSR) and block-diagonal constrained low-rank and sparse graph embedding (BLSGE). Firstly, the BLSR model is developed to reveal the intrinsic intra...
Robust Adaptive Low-Rank and Sparse Embedding for Feature Representation Lei Wang※ , Zhao Zhang ※, * , Senior Member, IEEE, Guangcan Liu ☆ , Member, IEEE, Qiaolin Ye ? , Member, IEEE, Jie Qin § , Member, IEEE, and Meng Wang∮ , Senior Member, IEEE ※ School of Computer Science...
Sparse representation and low-rank approximation are fundamental tools in fields as diverse as computer vision, computational biology, signal processing, natural language processing, and machine learning. Recent advances in sparse and low-rank modeling have led to increasingly concise descriptions of high...
Bearing fault diagnosisSparse and low-rank decompositiontime-frequency representationRobust principal component analysisVariable speed conditions... R Wang,H Fang,L Yu,... - 《Isa Transactions》 被引量: 0发表: 2021年 Time-Frequency Squeezing and Generalized Demodulation Combined for Variable Speed Beari...
Low rank and sparse representation (LRSR) with dual-dictionaries-based methods for detecting anomalies in hyperspectral images (HSIs) are proven to be effective. However, the potential anomaly dictionary is vulnerable to being contaminat... S Lin,M Zhang,XP Cheng,... - 《Remote Sens》 被引量...
For example, sparse/low-rank representation algorithms usually utilize the single-layer structures, so they fail to obtain the deep representations with more useful and valuable hidden hierarchical information discovered. With the fast development of deep learning and deep neural networks, it will be ...