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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About Me
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
Portfolio item number 1
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publications
Polarimetric Differential SAR Interferometry in an Arid Natural Environment Permalink
Published in International Journal of Applied Earth Observations and Geoinformation, 2017
Recommended citation: A. G. Mullissa, V. Tolpekin, A. Stein, and D. Perissin, “Polarimetric differential SAR interferometry in an arid natural environment,” Int. J. Appl. Earth Observ. Geoinf., vol. 59, pp. 9–18, Jul. 2017 http://adugnag.github.io/file/1-s2.0-S0303243417300454-main.pdf
Scattering property based contextual PolSAR speckle filter Permalink
Published in International Journal of Applied Earth Observations and Geoinformation, 2017
Recommended citation: A. G. Mullissa, V. Tolpekin, and A. Stein, “Scattering property based contextual PolSAR speckle filter,” Int. J. Appl. Earth Observ. Geoinf., vol. 63, pp. 78–89, Dec. 2017 http://adugnag.github.io/files/1-s2.0-S0303243417301502-main.pdf'
Quality Aspects of Distributed Scatterers in Polarimetric Differential SAR Interferometry Permalink
Published in University of Twente, 2017
Recommended citation: Mullissa, A. G. (2017). Quality aspects of distributed scatterers in polarimetric differential SAR interferometry. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC). http://adugnag.github.io/files/Adugna_Mullissa_PhD_Dissertation.pdf
PolSARNet: A Deep Fully Convolutional Network for Polarimetric SAR Image Classification Permalink
Published in IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 2019
Recommended citation: A. G. Mullissa, C. Persello and A. Stein, "PolSARNet: A Deep Fully Convolutional Network for Polarimetric SAR Image Classification," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing http://adugnag.github.io/files/PolSARNet_published.pdf
Polarimetry-Based Distributed Scatterer Processing Method for PSI Applications Permalink
Published in IEEE Transactions on Geoscience and Remote Sensing, 2019
Recommended citation: A. G. Mullissa, D. Perissin, V. A. Tolpekin and A. Stein, "Polarimetry-Based Distributed Scatterer Processing Method for PSI Applications," in IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 6, pp. 3371-3382 http://adugnag.github.io/files/08293685_small.pdf
Angular-Based Radiometric Slope Correction for Sentinel-1 on Google Earth Engine Permalink
Published in Remote Sensing, 2020
Recommended citation: Vollrath, A.; Mullissa, A.; Reiche, J. Angular-Based Radiometric Slope Correction for Sentinel-1 on Google Earth Engine. Remote Sens. 2020, 12, 1867. http://adugnag.github.io/files/Volli-mullissa_reiche_RS_2020.pdf
deSpeckNet: Generalizing Deep Learning-Based SAR Image Despeckling Permalink
Published in IEEE Transactions on Geoscience and Remote Sensing, 2020
Recommended citation: A. G. Mullissa, D. Marcos, D. Tuia, M. Herold and J. Reiche, "deSpeckNet: Generalizing Deep Learning-Based SAR Image Despeckling," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022 http://adugnag.github.io/files/deSpeckNet_published.pdf
Forest disturbance alerts for the Congo Basin using Sentinel-1 Permalink
Published in Environmental Research Letters, 2021
Recommended citation: J. Reiche, A. Mullissa, B. Slagter, Y. Gou, N.-E. Tsendbazar, C. Odongo-Braun, A. Vollrath, M. J. Weisse, F. Stolle, A. Pickens, et al., Forest disturbance alerts for the congo basin using sentinel-1, Environmental Research Letters 16 (2) (2021) 024005 http://adugnag.github.io/files/Reiche_2021_Environ._Res._Lett._16_024005.pdf
Despeckling Polarimetric SAR Data Using a Multistream Complex-Valued Fully Convolutional Network Permalink
Published in IEEE Geoscience and Remote Sensing Letters, 2021
Recommended citation: A. G. Mullissa, C. Persello and J. Reiche, "Despeckling Polarimetric SAR Data Using a Multistream Complex-Valued Fully Convolutional Network," in IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022 http://adugnag.github.io/files/cv-despecknet_published.pdf
Sentinel-1 SAR Backscatter Analysis Ready Data Preparation in Google Earth Engine Permalink
Published in Remote Sensing, 2021
Recommended citation: A. Mullissa, A. Vollrath, C. Odongo-Braun, B. Slagter, J. Balling,Y. Gou, N. Gorelick, J. Reiche, Sentinel-1 sar backscatter analysis ready data preparation in google earth engine, Remote Sensing 13 (10) (2021) 1954, doi:10.3390/rs13101954 http://adugnag.github.io/files/S1_ARD_remotesensing-13-01954.pdf
talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.