MixerCA: An efficient and accurate model for high-performance hyperspectral image classification (2025) – MBRSC Lab

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+971 4 5566 800 [email protected]

University of Dubai, UAE

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MBRSC Lab

Home
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- 2025
- 2024
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- 2021
- 2020
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- 2018
Projects
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Recent Posts

Examining sea levels forecasting using autoregressive and prophet models (2024)
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Alavikunhu Panthakkan Aleena Liifiya Alya Ahmed Al Maazmi Amjad Gawanmeh Ammar AlMheiri Anil G.R. Asmaa AlJanaahi Basma Samour Diena Al-Dogom Eisa Al-Shamsi Hamd Khan Haritha Harikrishnan Husameldin Mukhtar Hussain Al-Ahmad Ibrahim Al-Midfa Jaime Zabalza K. Schuckma Khalid AlSuwaidi Maisam Wahbah Marwa Chendeb El Rai Meera Rashid Al Shamsi Mina Al-Saad Mohammad Sami Zitouni Mohammed Alkhatib Mohammed Eshaq Muna Darwesh Naonori Ueda Nour Aburaed Rami Al-Ruzouq Razia Sulthana Abdul Kareem Regin R. Rida Gadhafi Saad Ali Amin Saeed Al Mansoori S Albesher Shadi Atalla Shahad Elshehabya Shaymaa Abushawish Shibani Hamsa Stephen Marshall Sunanda Mukherjee Tasnim Nazzal Wathiq Mansoor Yasmin Halawani Zakareyya Al-Shamsi

Mohammed Q. Alkhatib; Ali Jamali

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ConvViTMamba: efficient multiscale convolution, Transformer, and Mamba-based sequence modelling for hyperspectral image classification 2026-09-28
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SceneMixer: Exploring Convolutional Mixing Networks for Remote Sensing Scene Classification (2025) 2026-09-28

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Examining sea levels forecasting using autoregressive and prophet models (2024)

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