no code implementations • 11 Jul 2022 • Alan J. X. Guo, Cong Liang, Qing-Hu Hou
The Levenshtein distance is approximated by the squared Euclidean distance between the embedding vectors, which is fast calculated and clustering algorithm friendly.
no code implementations • 5 Apr 2021 • Alan J. X. Guo, Qing-Hu Hou, Ou wu
In recent years, Graph Neural Network (GNN) has bloomly progressed for its power in processing graph-based data.
no code implementations • 1 Apr 2020 • Alan J. X. Guo, Fei Zhu
Recent advances in neural networks have made great progress in the hyperspectral image (HSI) classification.
no code implementations • 4 Mar 2019 • Yi Liang, Xin Zhao, Alan J. X. Guo, Fei Zhu
To improve the classification performance in the context of hyperspectral image processing, many works have been developed based on two common strategies, namely the spatial-spectral information integration and the utilization of neural networks.
Ranked #8 on
Hyperspectral Image Classification
on Indian Pines
(Overall Accuracy metric)
General Classification
Hyperspectral Image Classification
+3
no code implementations • 31 Jan 2018 • Alan J. X. Guo, Fei Zhu
At the testing stage, by applying the discriminant model to the pixel-pairs generated by the test pixel and its neighbors, the local structure is estimated and represented as a customized convolutional kernel.
no code implementations • 20 Nov 2017 • Alan J. X. Guo, Fei Zhu
In this paper, we propose a spectral-spatial feature extraction and classification framework based on artificial neuron network (ANN) in the context of hyperspectral imagery.