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Akademický článek

Adaptive Learnable Spectral–Spatial Fusion Transformer for Hyperspectral Image Classification

Autor: Minhui Wang, Yaxiu Sun, Jianhong Xiang, Rui Sun, Yu Zhong

Publikováno v: Remote Sensing, Vol 16, Iss 11, p 1912 (2024)

In hyperspectral image classification (HSIC), every pixel of the HSI is assigned to a land cover category. While convolutional neural network (CNN)-based methods for HSIC have significantly enhanced performance, they encounter challenges in learning

Externí odkaz: https://doaj.org/article/5775b76a6de442ab8ba39898c0ff82e8

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Akademický článek

Joint Classification of Hyperspectral and LiDAR Data Based on Adaptive Gating Mechanism and Learnable Transformer

Autor: Minhui Wang, Yaxiu Sun, Jianhong Xiang, Rui Sun, Yu Zhong

Publikováno v: Remote Sensing, Vol 16, Iss 6, p 1080 (2024)

Utilizing multi-modal data, as opposed to only hyperspectral image (HSI), enhances target identification accuracy in remote sensing. Transformers are applied to multi-modal data classification for their long-range dependency but often overlook intrin

Externí odkaz: https://doaj.org/article/2a728cb7981149bfa261580372838c68

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Akademický článek

Heterogeneous Spectral-Spatial Network With 3D Attention and MLP for Hyperspectral Image Classification Using Limited Training Samples

Autor: Yaxiu Sun, Minhui Wang, Chen Wei, Yu Zhong, Jianhong Xiang

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 8702-8720 (2023)

Methods based on convolutional neural networks (CNNs) have become a vital offshoot for hyperspectral image (HSI) classification. In recent years, the 3-D CNN (3-DCNN) has become dominant due to its excellent capability of extracting features. However

Externí odkaz: https://doaj.org/article/806601b920c7444084445f83434afb55

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Akademický článek

Frequency Domain Analysis of Lossy and Non-Uniform Twisted Wire Pair

Autor: Yaxiu Sun, Jianli Wang, Wenliang Song, Rui Xue

Publikováno v: IEEE Access, Vol 7, Pp 52640-52649 (2019)

In the study of the frequency domain crosstalk for twisted pair, the traditional alternating inversion model is often built under the ideal condition of lossless and uniform media, ignoring the length of the twisted section. This paper focuses on the

Externí odkaz: https://doaj.org/article/84474ff6ee05435db1b41d2b8079dfdf

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Akademický článek

Robust Adaptive Beamforming against Signal Steering Vector Mismatch and Jammer Motion

Autor: Xiaojun Mao, Wenxing Li, Yingsong Li, Yaxiu Sun, Zhuqun Zhai

Publikováno v: International Journal of Antennas and Propagation, Vol 2015 (2015)

Since adaptive beamformer suffers from output performance degradation in the presence of interference nonstationarity and signal steering vector mismatch, a novel robust null broadening adaptive beamforming is proposed. The proposed method is realize

Externí odkaz: https://doaj.org/article/0f6c4bcd74274300bfe963a64c3f5625

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