Volume 11 - Volume 11
An Efficient Damage Relief System based on Image Processing and Deep Learning Techniques
Abstract
The Unmanned Aerial Vehicle (UAV) has been around for a long time but has been widely used
recently by humans. Their acceptance of various communications-based applications is expected to
improve coverage, compared to traditional ground-based solutions. In this paper, the Deep-learning
and Image Processing Process framework is expected to provide solutions to the various problems
already identified when UAVs are used for communication purposes. UAVs are used in disaster relief
because of their accessibility even in inaccessible places. In this paper, we propose research into
Deep learning and Image Processing strategies for UAVs. In deep learning is a form of machine
learning that teaches computers to do what comes naturally to people: learn by example and get a lot
of attention recently and for a good reason. It achieves previously impossible results. Image
processing is the process of performing a specific task on an image, finding an enhanced image or
extracting useful information from it. So our paper has the idea of using in depth face recognition
and photo processing a digital photo taken by the UAV to identify victims of rescue, overcoming back
to the latest UAV technology some of which include blurry images, unable to identify the victim when
there are too many objects and much more. The solution includes a variety of features that allow for
the distribution of images. It includes features and presentation of image detection and demonstrates
the effectiveness of drone use in damage applications.
Paper Details
PaperID: 1834
Author's Name: Dr.N. Kanya, Dr. Pacha Shobha Rani, Dr.S. Geetha, Dr.M. Rajkumar and G. Sandhiya
Volume: Volume 11
Issues: Volume 11
Keywords: Deep Learning, Image Processing, Unauthorized Car Vehicle.
Year: 2021
Month: April
Pages: 2124-2131