The Center for Information Technology and Public Policy (CITAPP)
International Institute of Information Technology Bangalore (IIITB)
organized a talk titled
Drones and Deep Learning for Agriculture
by
Dr. Ramesh KN
3:00 pm on 13th November 2019 (Wednesday)
Venue: Room A310, IIITB campus
26/C, Electronic City, Hosur Road, Bangalore
About the talk: Drones are set to change the face of Agriculture. Drone applications for agriculture include remote sensing from a drone, also known as Low Altitude Remote Sensing (LARS). LARS complements the traditional satellite based remote sensing. LARS provides the ability to observe crops closely. Plants, stalks, fruits and leaves can be observed in LARS, unlike in satellite imagery. Advancements in image processing is leading to the use of machine learning approaches in solving computer vision problems. LARS technology coupled with machine learning approaches to Computer Vision is drawing significant research interest in agriculture. The speaker will present his work in the application of drones and deep learning in crop studies, more specifically in the context of open field small holder farming, prevalent in India.
Speaker Bio: Dr. Ramesh KN has 17 years of experience at Infosys Technologies Ltd where he served as the Group Project Manager at its Product Engineering division. He has led R&D and product development activities for multiple telecom and datacom clients of Infosys. He then transitioned mid-career to pursue his research interests. He completed his Masters and Ph.D in Machine Learning. His research interest is in the area of Machine Learning (ML) approach to Computer Vision (CV). He has applied machine learning in analysis of aerial imagery acquired by remote sensing from Unmanned Aerial Systems (UAS),also known as Low Altitude Remote Sensing (LARS). LARS and the deep learning approach for LARS imagery analysis is an emerging area of research in an embryonic stage. He has carried out LARS applications for agriculture. Further, he has applied ML skills to solve real-world problems across a multitude of verticals such as the power sector and railways.