Скачать или смотреть Dr. Nagesh Kumar presents "Deep Learning & Geospatial Techniques in Agricultural Management"

Deep Learning (DL) is gaining considerable significance in various domains of agricultural management due to its capability to learn unknown non-linear processes, dimensionality reduction, data mining, and bid data processing. DL is subset of Machine Learning which is a subset of Artificial Intelligence. Common DL networks such as Deep Neural Networks (DNN), Convolution Neural Networks (CNN), Auto Encoders (AE), and Recurrent Neural Networks (RNN) will be discussed. DL applications in agricultural management with two case studies using microwave and hyperspectral remote sensing images will be presented. They include soybean crop acreage estimation and pear fruit orchard condition estimation. Deep Learning along with geospatial techniques can play a vital role in knowledge extraction by huge data mining which is essential for sustainable agricultural management.

Dr. Kumar completed his term as a Curtis Visiting Professor in Civil and Construction Engineering at Purdue University in May of 2025, while on sabbatical from IISc Bangalore, where he’s been a Civil Engineering Professor since 2002. At present, Dr. Kumar is visiting the Purdue College of Agriculture, under the OVDF program of ANRF, Govt. of India. He earned his Ph.D. from IISc in 1992 and previously worked at IIT Kharagpur and the National Remote Sensing Centre.

Special thanks to Nagesh Kumar. Video editing by: Melinda Smith

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