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Unsupervised Spatial-spectral Network Learning for Hyperspectral Compressive Snapshot Reconstruction
Hyperspectral compressive imaging takes advantage of compressive sensing...
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Meta-Learning with Network Pruning
Meta-learning is a powerful paradigm for few-shot learning. Although wit...
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Hyperspectral Image Classification with Attention Aided CNNs
Convolutional neural networks (CNNs) have been widely used for hyperspec...
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Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection
Co-saliency detection aims to discover the common and salient foreground...
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Dual Temporal Memory Network for Efficient Video Object Segmentation
Video Object Segmentation (VOS) is typically formulated in a semi-superv...
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Classification of Hyperspectral and LiDAR Data Using Coupled CNNs
In this paper, we propose an efficient and effective framework to fuse h...
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Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network
Due to a variety of motions across different frames, it is highly challe...
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Deep Object Co-segmentation via Spatial-Semantic Network Modulation
Object co-segmentation is to segment the shared objects in multiple rele...
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Cascaded Recurrent Neural Networks for Hyperspectral Image Classification
By considering the spectral signature as a sequence, recurrent neural ne...
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Matrix Completion with Nonuniform Sampling: Theories and Methods
Prevalent matrix completion theories reply on an assumption that the loc...
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Fast and Robust Subspace Clustering Using Random Projections
Over the past several decades, subspace clustering has been receiving in...
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Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification
This paper proposes a novel deep learning framework named bidirectional-...
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Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Iterative Hard Thresholding (IHT) is a class of projected gradient desce...
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Unsupervised Video Segmentation via Spatio-Temporally Nonlocal Appearance Learning
Video object segmentation is challenging due to the factors like rapidly...
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Learning Multi-Scale Deep Features for High-Resolution Satellite Image Classification
In this paper, we propose a multi-scale deep feature learning method for...
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Adaptive Deep Pyramid Matching for Remote Sensing Scene Classification
Convolutional neural networks (CNNs) have attracted increasing attention...
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Visual Tracking via Boolean Map Representations
In this paper, we present a simple yet effective Boolean map based repre...
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Elastic Net Hypergraph Learning for Image Clustering and Semi-supervised Classification
Graph model is emerging as a very effective tool for learning the comple...
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Adaptive Compressive Tracking via Online Vector Boosting Feature Selection
Recently, the compressive tracking (CT) method has attracted much attent...
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Robust Visual Tracking via Convolutional Networks
Deep networks have been successfully applied to visual tracking by learn...
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