يعرض 1 - 10 نتائج من 265 نتيجة بحث عن '"Oommen, Thomas"', وقت الاستعلام: 1.06s تنقيح النتائج
  1. 1
    مؤتمر
    MarsLS-Net: Martian Landslides Segmentation Network and Benchmark Dataset

    المؤلفون: Paheding, Sidike, Reyes, Abel A., Rajaneesh, A., Sajinkumar, K.S., Oommen, Thomas

    المصدر: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) WACV Applications of Computer Vision (WACV), 2024 IEEE/CVF Winter Conference on. :8221-8230 Jan, 2024

    Relation: 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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  2. 2
    مؤتمر
    C-PLES: Contextual Progressive Layer Expansion with Self-attention for Multi-class Landslide Segmentation on Mars using Multimodal Satellite Imagery

    المؤلفون: Reyes, Abel A., Paheding, Sidike, Rajaneesh, A., Sajinkumar, K.S., Oommen, Thomas

    المصدر: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) CVPRW Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 IEEE/CVF Conference on. :354-364 Jun, 2023

    Relation: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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  3. 3
    دورية أكاديمية
    Suitability of the height above nearest drainage (HAND) model for flood inundation mapping in data-scarce regions: a comparative analysis with hydrodynamic models

    المؤلفون: Thalakkottukara, Navin TonyAff1, IDs1214502301218x_cor1, Thomas, Jobin, Watkins, Melanie K., Holland, Benjamin C., Oommen, Thomas, Grover, Himanshu

    المصدر: Earth Science Informatics. 17(3):1907-1921

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  4. 4
    مؤتمر
    GAF-NAU: Gramian Angular Field encoded Neighborhood Attention U-Net for Pixel-Wise Hyperspectral Image Classification

    المؤلفون: Paheding, Sidike, Reyes, Abel A., Kasaragod, Anush, Oommen, Thomas

    المصدر: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) CVPRW Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 IEEE/CVF Conference on. :408-416 Jun, 2022

    Relation: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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  5. 5
    تقرير
    Individual Fairness under Uncertainty

    المؤلفون: Zhang, Wenbin, Wang, Zichong, Kim, Juyong, Cheng, Cheng, Oommen, Thomas, Ravikumar, Pradeep, Weiss, Jeremy

    مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computers and Society

    URL الوصول: http://arxiv.org/abs/2302.08015

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  6. 6
    دورية أكاديمية
    PyLandslide: A Python tool for landslide susceptibility mapping and uncertainty analysis

    المؤلفون: Basheer, Mohammed, Oommen, Thomas

    المصدر: In Environmental Modelling and Software June 2024 177

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  7. 7
    دورية أكاديمية

    لا يتم عرض هذه النتيجة على الضيوف.

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  8. 8
    مؤتمر
    Monitoring and modeling tailings impoundment settlement near Great Salt Lake (UTAH) using multi-platform time-series InSAR observations

    المؤلفون: Hu, Xie, Lu, Zhong, Oommen, Thomas, Wang, Teng, Kim, Jinwoo

    المصدر: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Geoscience and Remote Sensing Symposium (IGARSS), 2017 IEEE International. :40-43 Jul, 2017

    Relation: IGARSS 2017 - 2017 IEEE International Geoscience and Remote Sensing Symposium

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  9. 9
    كتاب إلكتروني
    Significance of the Spatial Resolution of DEM in Regional Slope Stability Analysis Enguri Dam, Republic of Georgia

    المؤلفون: Nichols, IanAff4, Gierke, John S.Aff4, Oommen, ThomasAff4, Acciaro, Maria DilettaAff4, Aff5

    المساهمون: Bonali, Fabio Luca, editorAff1, Pasquaré Mariotto, Federico, editorAff2, Tsereteli, Nino, editorAff3

    المصدر: Building Knowledge for Geohazard Assessment and Management in the Caucasus and other Orogenic Regions. :281-300

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  10. 10
    دورية أكاديمية
    Automated Flood Prediction along Railway Tracks Using Remotely Sensed Data and Traditional Flood Models.

    المؤلفون: Zakaria, Abdul-Rashid, Oommen, Thomas, Lautala, Pasi

    المصدر: Remote Sensing; Jul2024, Vol. 16 Issue 13, p2332, 22p

    مصطلحات موضوعية: FLOOD forecasting, ARTIFICIAL neural networks, RAINFALL, FLOODS, SUPPORT vector machines, MACHINE learning

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