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International Journal of Remote Sensing Volume 41, 2020 - Issue 18
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Research Article

A hyperspectral anomaly detection framework based on segmentation and convolutional neural network algorithms

Benyamin HosseinySchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranORCID Iconhttps://orcid.org/0000-0002-8212-2639
ORCID Icon &
Reza Shah-HosseiniSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-7552-5392
ORCID Icon
Pages 6946-6975 | Received 31 Jul 2019, Accepted 15 Dec 2019, Published online: 30 Jun 2020

Citations (14)

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Yating Xu, Kai Zhao, Liangang Zhang, Mengyao Zhu & Dan Zeng. (2023) Hyperspectral anomaly detection with vision transformer and adversarial refinement. International Journal of Remote Sensing 44:13, pages 4034-4057.
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Minkai Hou, Tao Wang, Yanzhao Su, Yanping Cai & Jiping Cao. (2022) Hyperspectral anomaly detection based on adaptive weighting method combined with autoencoder and convolutional neural network. International Journal of Remote Sensing 43:7, pages 2617-2637.
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Bangbang Ge, Chunping Hou, Yang Liu, Zhipeng Wang & Ruiheng Wu. (2021) Anomaly detection of power line insulator from aerial imagery with attribute self-supervised learning. International Journal of Remote Sensing 42:23, pages 8819-8839.
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Sukanta Roy, Sumit Pathak & Subbaramajois Narasipur Omkar. (2021) Automated mineralogical anomaly detection using a categorization of optical maturity trend at lunar surface. International Journal of Remote Sensing 42:21, pages 8262-8297.
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Orhan Torun & Seniha Esen Yuksel. (2021) Unsupervised segmentation of LiDAR fused hyperspectral imagery using pointwise mutual information. International Journal of Remote Sensing 42:17, pages 6461-6476.
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Lili Zhang & Baozhi Cheng. (2021) A combined model based on stacked autoencoders and fractional Fourier entropy for hyperspectral anomaly detection. International Journal of Remote Sensing 42:10, pages 3611-3632.
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Xiaoyu Cheng, Zhouyin Cai, Jia Li, Maoxing Wen, Yueming Wang & Dan Zeng. (2021) A spatial-spectral clustering-based algorithm for endmember extraction and hyperspectral unmixing. International Journal of Remote Sensing 42:5, pages 1948-1972.
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Articles from other publishers (7)

Benyamin Hosseiny, Masoud Mahdianpari, Mohammadali Hemati, Ali Radman, Fariba Mohammadimanesh & Jocelyn Chanussot. (2024) Beyond Supervised Learning in Remote Sensing: A Systematic Review of Deep Learning Approaches. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17, pages 1035-1052.
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Wuxia Zhang, Huibo Guo, Shuo Liu & Siyuan Wu. (2023) Attention-Aware Spectral Difference Representation for Hyperspectral Anomaly Detection. Remote Sensing 15:10, pages 2652.
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Shuhe Han. (2022) Research on Online Social Network Information Leakage-Tracking Algorithm Based on Deep Learning. Computational Intelligence and Neuroscience 2022, pages 1-11.
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Xing Hu, Chun Xie, Zhe Fan, Qianqian Duan, Dawei Zhang, Linhua Jiang, Xian Wei, Danfeng Hong, Guoqiang Li, Xinhua Zeng, Wenming Chen, Dongfang Wu & Jocelyn Chanussot. (2022) Hyperspectral Anomaly Detection Using Deep Learning: A Review. Remote Sensing 14:9, pages 1973.
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Yunsong Li, Tao Jiang, Weiying Xie, Jie Lei & Qian Du. (2022) Sparse Coding-Inspired GAN for Hyperspectral Anomaly Detection in Weakly Supervised Learning. IEEE Transactions on Geoscience and Remote Sensing 60, pages 1-11.
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Xiaorun Li, Shaoqi Yu, Shuhan Chen & Liaoying Zhao. (2022) Normalizing Flow-Based Probability Distribution Representation Detector for Hyperspectral Anomaly Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15, pages 4885-4896.
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Benyamin Hosseiny, Heidar Rastiveis & Saeid Homayouni. (2020) An Automated Framework for Plant Detection Based on Deep Simulated Learning from Drone Imagery. Remote Sensing 12:21, pages 3521.
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