2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

2020 IEEE International Geoscience and Remote Sensing Symposium

September 26 - October 2, 2020 • Virtual Symposium

My IGARSS 2020 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)

Paper Detail

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Paper Title UAV BASED REMOTE SENSING FOR TASSEL DETECTION AND GROWTH STAGE ESTIMATION OF MAIZE CROP USING MULTISPECTRAL IMAGES
Paper IdentifierWE2.R18.5
Authors Ajay Kumar, Mahesh Taparia, P. Rajalakshmi, Indian Institute of Technology Hyderabad Telangana India, India; Wei Guo, International Field Phenomics Research Laboratory, Institute for Sustainable Agro-ecosystem Services, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan, Japan; Balaji Naik, Balram Marathi, Professor Jayashankar Telangana State Agricultural University (PJTSAU), India; Uday Desai, Indian Institute of Technology Hyderabad Telangana India, India
Session Deep and Semantic Learning for Object Detection
Session Time Wed, 30 Sep, 14:30 - 16:30 UTC
Wed, 30 Sep, 22:30 - 00:30 China Standard Time (UTC +8)
Wed, 30 Sep, 16:30 - 18:30 Central Europe Time (UTC +2)
Wed, 30 Sep, 07:30 - 09:30 Pacific Daylight Time (UTC -7)
Presentation Time
[This Paper Only]		 Wed, 30 Sep, 15:10 - 15:20 UTC
Wed, 30 Sep, 23:10 - 23:20 China Standard Time (UTC +8)
Wed, 30 Sep, 17:10 - 17:20 Central Europe Time (UTC +2)
Wed, 30 Sep, 08:10 - 08:20 Pacific Daylight Time (UTC -7)
Presentation Mode Virtual
Topic Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR): Object Detection and Recognition