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An unsupervised opinion summarization model fused joint attention and dictionary learning
Unsupervised opinion summarization is the technique of automatically generates summaries without gold reference, and the summaries that reflects...
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Performance analysis on dictionary learning and sparse representation algorithms
Theoretically, the Super-Resolution (SR) reconstruction scheme is a method which is performed by many applications nowadays for the purpose of...
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Salient double reconstruction-based discriminative projective dictionary pair learning for crowd counting
Crowd counting is one of the most fundamental tasks in the field of computer vision and dictionary learning has been successfully applied to the...
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Discriminative Deep Non-Linear Dictionary Learning for Visual Object Tracking
Deep neural networks have been widely applied to visual tracking and obtained significant improvements in tracking accuracy and robustness. But some...
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Structured classifier-based dictionary pair learning for pattern classification
The supervised dictionary learning methods have made considerable achievements in the field of pattern recognition. In order to make the learned...
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LexiSNTAGMM: an unsupervised framework for sentiment classification in data from distinct domains, synergistically integrating dictionary-based and machine learning approaches
Sentiment analysis, an extensively explored area in the realm of natural language processing, holds the utmost importance for a wide range of...
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Distributed Analysis Dictionary Learning Using a Diffusion Strategy
We consider the problem of distributed dictionary learning which aims to learn a global dictionary from data geographically distributed on nodes of a...
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MRI Image Fusion Based on Optimized Dictionary Learning and Binary Map Refining in Gradient Domain
The insufficient ability of edge feature extraction and high complexity limit the ability of sparse representation to obtain better medical image...
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Image Super-Resolution via Deep Dictionary Learning
The method of image super-resolution reconstruction through a dictionary usually only uses a single-layer dictionary, which not only fails to extract...
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Dictionary reduction in sparse representation-based classification of motor imagery EEG signals
Recently, sparse representation-based classification has turned into a successful technique for motor imagery electroencephalogram signal analysis....
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Meta-DZSL: a meta-dictionary learning based approach to zero-shot recognition
Zero-shot learning is an essential paradigm for learning novel concepts, i.e., those whose instances were unavailable during training. Dictionary...
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Low-dose CT iterative reconstruction based on image block classification and dictionary learning
For conventional image reconstruction based on dictionary learning in low-dose computed tomography (CT) imaging, all image blocks are represented by...
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Dual transform based joint learning single channel speech separation using generative joint dictionary learning
Single channel speech separation (SS) is highly significant in many real-world speech processing applications such as hearing aids, automatic speech...
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Real-time textile fabric flaw inspection system using grouped sparse dictionary
Fabric surface flaw inspection is essential for textile quality control, and it is demanding to replace human inspectors with the automatic machine...
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Dictionary cache transformer for hyperspectral image classification
The spectral anomalies, limited training samples, and noisy training labels pose significant challenges to accurately classifying hyperspectral...
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Cross-domain EEG signal classification via geometric preserving transfer discriminative dictionary learning
EEG signal classification is a key technology for EEG signal processing and identification systems. Dictionary learning has shown excellent...
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Weak Correlation-Based Discriminative Dictionary Learning for Image Classification
Currently, representation-based learning is widely used in image classification because of its good mathematical interpretability. However, when the...
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Fast data-free model compression via dictionary-pair reconstruction
Deep neural network (DNN) obtained satisfactory results on different vision tasks; however, they usually suffer from large models and massive...
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Order-Sensitivity Sentiment dictionary of word sequences containing intensifiers
There are many natural language processing methods that can be used to analyze audio, image, and video captions and improve the accuracy of...
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Dictionary learning and face recognition based on sample expansion
Dictionary learning has become a research hotspot. How to construct a robust dictionary is a key issue. In face recognition problem, differences in...
