Hyperspectral Unmixing Using Deep Convolutional Autoencoders in a Supervised Scenario

Author:

Khajehrayeni Farshid,Ghassemian HassanORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Cited by 64 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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2. Two-Stream Autoencoder-Based Hyperspectral Unmixing using Hapke Model;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

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4. Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package;IEEE Transactions on Geoscience and Remote Sensing;2024

5. Pixel-to-Abundance Translation: Conditional Generative Adversarial Networks Based on Patch Transformer for Hyperspectral Unmixing;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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