Technical Program

Session Detail

Session Title FR3.R11: Digital Agriculture with Machine Learning and Remote Sensing II
Presentation Mode Oral
Session Time Friday, 02 August, 13:40 - 15:20
Location Room 419
Session ChairDharmendra Singh, Indian Institute of Technology, Roorkee

FR3.R11.1: MAXIMUM MEMBERSHIP FRACTION BASED PURE PIXEL ASSESSMENT APPROACH FOR HYPERSPECTRAL DATA ANALYSIS USING DEEP LEARNING
         S. N. Chaudhri; Indian Institute of Technology BHU (Banaras Hindu University)
         N. S. Rajput; Indian Institute of Technology BHU (Banaras Hindu University)
         K. P. Singh; Indian Institute of Technology BHU (Banaras Hindu University)
         D. Singh; Indian Institute of Technology, Roorkee

FR3.R11.2: IMPROVED UTILIZATION OF POLSAR POLARIZATION SIGNATURES USING CONVOLUTIONAL-DEEP NEURAL NETS FOR LAND COVER CLASSIFICATION
         Gopal Phartiyal; Indian Institute of Technology Roorkee
         Dharmendra Singh; Indian Institute of Technology Roorkee
         Nicolas Brodu; INRIA
         Hussein Yahia; INRIA

FR3.R11.3: A STEP TOWARDS DIGITAL AGRICULTURE FOR DEVELOPMENT OF OBJECT BASED PHENOLOGY APPROACH TO CLASSIFY SUGARCANE AND PADDY CROPS USING MULTISENSOR DATA
         Deepak Murugan; IIT Roorkee
         Dharmendra Singh; IIT Roorkee

FR3.R11.4: DEVELOPMENT OF MACHINE LEARNING BASED APPROACH FOR COMPUTING OPTIMAL VEGETATION INDEX WITH THE USE OF SENTINEL-2 AND DRONE DATA
         Ankush Agarwal; IIT Roorkee
         Sandeep Kumar; IIT Roorkee
         Dharmendra Singh; IIT Roorkee

FR3.R11.5: IN-SEASON PREDICTION OF CROP TYPES IN THE US GREAT PLAINS USING SEQUENCE BASED STOCHASTIC MODELS AND DEEP LEARNING
         Subit Chakrabarti; Indigo Agriculture
         Rob Braswell; Indigo Agriculture
         Nick Malizia; Indigo Agriculture
         Damien Sulla-Menashe; Indigo Agriculture
         Tina Cormier; Indigo Agriculture
         Mark Friedl; Boston University