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Workshop 1: Practical Deep Learning Based Object Detection on Aerial Images 

Object Detection Using Deep Learning Models:

The objective of the workshop is to demonstrate the drone based common object detections which can be applied to satellite images too for common object detections.

Why this workshop is important:

Locating common objects like pedestrians, bikers and cars on roads is essential for city surveillance. This workshop presents a way that can help citywide speed up the pedestrian, bikers and car detection process by the use of drones. Any high number of presence of people, or cars can alert the authorities to take further actions. Drone technology is advancing at a rapid pace, improving drone capabilities whilst an increasingly competitive market is driving prices down. Drone capability is having an overall positive impact on society with its focus on usage in crisis and emergency response, search and rescue, automated shipping, the film industry, farming, environmental management, etc. This increases public surveillance and helps the concerned authorities to develop smart cities. Hands on using deep learning techniques of Yolov5 and other object detection techniques can help the system to detect common objects across the cities. 

Who should attend this workshop?

All students, teachers, professors and professionals working in research, academics, computer vision, smart city projects. This workshop provides resources to design deep learning processes and to improve deep learning to achieve desired outcomes. Participant experience will be used throughout the workshop to illustrate principles.

What participants will learn during the workshop:

At the end of the all-day workshop, participants should be able to:

      Identify the scope of deep learning in object detection frameworks.

      Describe ways to apply deep Learning for common object detections.

      Hands on 2: using Yolov5 for real world object detection in aerial images.

Outline for Deep Learning Training (time for breaks and lunch will be included)

 Welcome and workshop overview

This orientation includes a participatory activity to introduce the concept of deep learning especially Convolution Neural Network for approaching problems in computer vision domain.

1.       Deep Learning—How does it work in the real world? 

2.    This interactive power point presentation using key pad poling technology    demonstrates how Deep Learning is used to build  effective solutions.

3.    Introduction to Satellite Images—Multispectral, Hyperspectral and RGB Images.

4.    Introduction to various datasets.

5.    Choosing the right datasets for our real-world examples.

6.    Training the datasets.

7.    Interpreting the results.

8.    Inferencing the datasets.

9.    The Challenges of Change

Learn how you can design your projects to take advantage of powerful techniques of deep learning and apply it in your real-world applications. Workshop materials will be provided electronically during the workshop. 

Presenter Qualifications

   Gaurav Tripathi received his M. Tech. degree in Information Technology (Specialization: Artificial Intelligence). Indian Institute of Information Technology, Allahabad in 2007 PhD from Delhi Technological University, India. He currently works as senior scientist at Bharat Electronics Ltd. India. His research interest includes Internet of Things, Deep Learning, Convolutional Neural Networks based Computer Vision, Fog computing.

Contact information:

Gaurav Tripathi, Ph.D.

Senior Scientist,

Central Research Lab,

Bharat Electronics Limited,

India

gauravtripathy@gmail.com