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DTSTART;TZID=Asia/Dubai:20210504T100000
DTEND;TZID=Asia/Dubai:20210504T110000
DTSTAMP:20240513T045026Z
CREATED:20210504T095538Z
LAST-MODIFIED:20240513T045026Z
UID:3460-1620122400-1620126000@www.esgrs.ae
SUMMARY:Semantic Segmentation of Roads in Satellite Imagery
DESCRIPTION:Remote sensing is a field that is constantly growing due to its importance in applications related to urban planning\, risk assessment\, resource exploration\, and disaster management. Some of the most highly researched topics in the area of remote sensing include Land Cover Land Use (LCLU)\, object detection\, scene classification\, and semantic segmentation. Nowadays\, researchers are looking into automating these tasks\, as performing them manually is time and cost inefficient. Therefore\, Deep Learning (DL) algorithms have been utilized for remote sensing and image processing tasks in the recent years. Many studies proved efficiency of DL algorithms\, however\, several challenges remain unsolved. In particular\, semantic segmentation is one of the challenging tasks that is under heavy demand in the field of remote sensing. For this research study\, semantic segmentation is applied to extract roads from satellite images. Road mapping is an essential first step in several applications that include transportation\, traffic management\, and city planning. Extracting roads efficiently and accurately will in turn boost the overall outcome of the aforementioned applications. U-Net is the state-of-the-art Convolutional Neural Networks (CNN) that perform semantic segmentation. This network will be trained using publically available Massachusetts dataset. The accuracy and loss of all experiments will be reported and sample results from the dataset will be demonstrated.\n\n\n    \n    \n    \n\n                \n        \n            \n\n                \n                                \n                    \n                        \n                            \n                                \n                                ENG. MINA AL-SAADRESEARCH ASSISTANT @MBRSC LAB - UNIVERSITY OF DUBAIMina Al-Saad is a Research Assistant at Mohammed Bin Rashid Space Center (MBRSC) Lab at university of Dubai. She received her BSc in Laser and Optoelectronics Engineering from Al-Nahrain University\, Iraq in 2009 and received her MSc in Laser and Optoelectronics Engineering from Al-Nahrain University\, Iraq (2012). Her research interests include: Geographic information system (GIS) and remote sensing\, Autonomous Object Detection\, Semantic Segmentation\, and Satellite Calibration and Validation. \n\n                            \n                        \n                    \n\n                    \n                        \n            \n\n        \n                \n        \n            No Results Found
URL:https://www.esgrs.ae/event/semantic-segmentation-of-roads-in-satellite-imagery/
CATEGORIES:2021,Webinars
ATTACH;FMTTYPE=image/jpeg:https://www.esgrs.ae/wp-content/uploads/2023/07/MicrosoftTeams-image-5.jpg
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DTSTART;TZID=Asia/Dubai:20210520T100000
DTEND;TZID=Asia/Dubai:20210520T110000
DTSTAMP:20240513T050345Z
CREATED:20210520T095530Z
LAST-MODIFIED:20240513T050345Z
UID:3463-1621504800-1621508400@www.esgrs.ae
SUMMARY:Protecting Satellite Images Against Attacks using AI and Image Processing Techniques
DESCRIPTION:Satellite imagery is a pivotal source of valuable information for monitoring our planet along with natural resources. However\, these images have an extreme acquisition cost. Nowadays\, with the widespread of the advanced technology\, unauthorized ordinary people can access these data\, modify their content and utilize them illegally. Therefore\, there is a massive demand for providing secure storage and transmission of such data. Hence\, digital watermarking has been introduced for overcoming this illegitimate practice.\n\n\n    \n    \n    \n\n                \n        \n            \n\n                \n                                \n                    \n                        \n                            \n                                \n                                DR. ALAVIKUNHU PANTHAKKANASSISTANT PROFESSORDr. Alavikunhu Panthakkan is a dynamic research scientist in electronics engineering and image signal processing. His research interests are in the areas of engineering education\, copyright protection\, authentication\, medical image processing\, video signal processing and artificial neural network. He received bachelor degree (B.Tech) in electronics and communication engineering\, master degree (M.Tech) in electronics engineering and Ph.D. in electronics engineering. He has 4 years industrial experience and 7 years of teaching/research experience. He has published 20 papers in international conferences and journals. He is a member of Institute of Electrical and Electronic Engineers (IEEE)\, member of Institution of Engineers (India) (MIE)\, member of International Association of Engineers (IAENG)\, member of International Association of Computer and Information Technology (IACSIT) and member of Institute of Research Engineers and Doctors (IRED). \n\n                            \n                        \n                    \n\n                    \n                        \n            \n\n        \n                \n        \n            No Results Found
URL:https://www.esgrs.ae/event/protecting-satellite-images-against-attacks-using-ai-and-image-processing-techniques/
CATEGORIES:2021,Webinars
ATTACH;FMTTYPE=image/jpeg:https://www.esgrs.ae/wp-content/uploads/2023/07/watermarking.jpg
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