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Yue Wu
Researcher at Xidian University
Publications - 54
Citations - 1879
Yue Wu is an academic researcher from Xidian University. The author has contributed to research in topics: Image registration & Feature (computer vision). The author has an hindex of 17, co-authored 54 publications receiving 983 citations.
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Remote Sensing Image Registration With Modified SIFT and Enhanced Feature Matching
TL;DR: A new gradient definition is introduced to overcome the difference of image intensity between the remote image pairs and an enhanced feature matching method by combining the position, scale, and orientation of each keypoint is introduction to increase the number of correct correspondences.
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A Novel Point-Matching Algorithm Based on Fast Sample Consensus for Image Registration
TL;DR: An improved random sample consensus algorithm called fast sample consensus (FSC), which divides the data set in RANSAC into two parts: the sample set and the consensus set, and an iterative method to increase the number of correct correspondences is put forward.
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Double-Branch Multi-Attention Mechanism Network for Hyperspectral Image Classification
TL;DR: A Double-Branch Multi-Attention mechanism network (DBMA) is proposed for HSI classification which has two branches to extract spectral and spatial feature respectively which can reduce the interference between the two types of feature.
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Unsupervised Feature Extraction in Hyperspectral Images Based on Wasserstein Generative Adversarial Network
TL;DR: A novel modified generative adversarial network (GAN) is proposed to train a DL-based feature extractor without supervision, and replaces the original Jensen–Shannon divergence with the Wasserstein distance, aiming to mitigate the unstability and difficulty of the training of GAN frameworks.
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A Novel Two-Step Registration Method for Remote Sensing Images Based on Deep and Local Features
TL;DR: An effective coarse-to-fine strategy is introduced and a new two-step registration method based on deep and local features based on a convolutional neural network is developed, which can apparently increase the correct correspondences, can improve the ratio of correct Correspondences, and is highly robust and accurate.