Shivangi Srivastava

About

My research focuses on deep learning models to solve problems such as multi-modal data fusion, semantic segmentation, and continual learning, among others. I primarily use remote sensing aerial/satellite imagery, terrestrial pictures from social media along with geospatial information to test my models.

Employment

Employment history is unavailable.

Education

• Wageningen University & Research PhD
  2017 - 2020
• University of Zurich PhD
  2015 - 2017
• École Centrale Paris Masters by Research in Mathematics, Vision and Learning (MVA)
  2014 - 2015
• Delhi Technological University Bachelor of Engineering student
  2005 - 2009

Projects & Funding

Projects & funding information is unavailable.

Publications (7)

• OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing
  IEEE Geoscience and Remote Sensing Magazine 2020 DOI: 10.1109/mgrs.2020.2994107
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• Adaptive Compression-based Lifelong Learning
  30th British Machine Vision Conference 2019
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• Understanding urban landuse from the above and ground perspectives: A deep learning, multimodal solution
  Remote Sensing of Environment 2019 DOI: 10.1016/j.rse.2019.04.014
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• Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data
  International Journal of Geographical Information Science 2018 DOI: 10.1080/13658816.2018.1542698
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• Land-use characterisation using Google Street View pictures and OpenStreetMap
  21st AGILE Conference on Geographic Information Science 2018
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• Joint height estimation and semantic labeling of monocular aerial images with CNNS
  2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2017 DOI: 10.1109/igarss.2017.8128167
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• A Novel Approach for Edge Detection using AntColony Otimization and Fuzz Derivative Technique
  2009 IEEE International Advance Computing Conference 2009 DOI: 10.1109/iadcc.2009.4809187
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