Deep Learning Algorithms for Drone Data Analysis

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  Date and Time

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  • Date: 27 Apr 2024
  • Time: 03:00 PM to 04:00 PM
  • All times are (UTC+05:30) Chennai
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  • Starts 12 April 2024 11:00 AM
  • Ends 27 April 2024 04:00 PM
  • All times are (UTC+05:30) Chennai
  • No Admission Charge

  Speakers

Shyam Lal of NITK Surathkal

Topic:

Deep Learning Algorithms for Drone Data Analysis

Biography:

Shyam Lal received Ph.D. degree in Digital Image Processing from Department of Electronics & Communication Engineering, Birla Institute of Technology, Mesra, Ranchi (Jharkhand), India. Currently he is working as Associate Professor in the Department of Electronics & Communication Engineering, NITK, Surathkal, Mangalore (Karnataka), India.  He was Visiting Professor at University of Pavia, Italy, Visiting Fellow at Tokyo Institute of Technology, Tokyo. He is CEO and Director of M/S AIQUANTUM SMART SOLUTION PRIVATE LIMITED, STEP-NITK SURATHKAL, MANGALURU, KARNATAKA, INDIA.  He has more than 20 years of Teaching & Research experience. He has supervised 07 Ph.D. students and currently 06 Ph.D. students are working under his supervision. He has received Early Career Research Award (Young Scientist) in 2017 from SERB, DST, Young Faculty Research Fellow (YFRF) in 2019, MeitY, GoI, and also recipient of Outstanding Research Publication award 2024 from VGST, Government of Karnataka.  His area of interest includes Quantum Computing Algorithms with Applications, Artificial Intelligence, Machine Learning, Deep Learning and Optimization Algorithms with Applications in Radiology Image Processing, Histopathology Image Processing, Satellite Image Processing, IoT and Cyber security, and Manufacturing Industry.

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Agenda

Drone data analysis and visualization can help to enhance products and services more effectively with customers and gain a competitive edge in the current market. By processing and transforming drone data, useful information such as measurements, counts, classifications, patterns, trends, and anomalies can be extracted. Drone data can be also used for creating interactive maps, 3D models, charts, and reports. High-resolution aerial data are becoming more readily available for various tasks, including maintenance, surveying, mapping, and monitoring. The drone data will be analysed using advanced algorithms and machine learning models can be trained on drone data to automate tasks like land cover mapping, flood monitoring, change detection, object recognition, anomaly detection, etc. Due to the learning capabilities of Deep learning (DL) from raw data, DL technology originated from artificial neural network (ANN), and has become a hot topic in the context of drone data analysis. This expert talk cover’s introduction of drone data acquisition, done data analysis, publicly available done datasets, and applications of deep learning algorithms for image-based and pixel-based done data analysis. Finally, future research direction on advance algorithms for done data analysis.