FR3.R7.3

DEEP LEARNING MODEL FOR MINIMAL AREA DETECTION OF WEED PATCHES IN UAV IMAGERY

Vyomika Singh, Indian Institute of Technology Roorkee, Roorkee, India; Raghav Luthra, Jaypee University of Information Technology, India; Laxman Singh Khangarot, Dharmendra Singh, Indian Institute of Technology Roorkee, India
Session:
FR3.R7: Synergistic Use of Remote Sensing, IoT, and AI in Agriculture II Oral
Track:
Community-Contributed Sessions
Location:
Room G
Presentation Time:
Fri, 21 Jul, 13:12 - 13:24 Pacific Time (UTC -7)
Session Co-Chairs:
Pietro Mastro, Institute for Electromagnetic Sensing of the Environment (IREA), Italian National Research Council and Claudia Spinetti, Istituto Nazionale di Geofisica e Vulcanologia
Session Manager:
Zhoobin Rahimi
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Session FR3.R7
FR3.R7.2: USE OF SAR BASED REGRESSORS FOR LEAF AREA INDEX (LAI) SPATIAL/TEMPORAL FILLING: A MACHINE LEARNING (ML)-BASED OUTLOOK
Pietro Mastro, Mirco Boschetti, Margherita De Peppo, Antonio Pepe, Institute for Electromagnetic Sensing of the Environment (IREA), Italian National Research Council, Italy
FR3.R7.3: DEEP LEARNING MODEL FOR MINIMAL AREA DETECTION OF WEED PATCHES IN UAV IMAGERY
Vyomika Singh, Indian Institute of Technology Roorkee, Roorkee, India; Raghav Luthra, Jaypee University of Information Technology, India; Laxman Singh Khangarot, Dharmendra Singh, Indian Institute of Technology Roorkee, India
FR3.R7.4: IMPACT OF PERMUTED SPECTRAL NEIGHBORHOOD OF HIGH-DIMENSIONAL MSTS RS DATA ON CROP CLASSIFICATION PERFORMANCE WITH DNN MODELS
Gopal Singh Phartiyal, Laxman Singh Khangarot, Dharmendra Singh, Indian Institute of Technology Roorkee, India
Resources
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