Real-Time Automatic Investigation of Indian Roadway Animals by 3D Reconstruction Detection Using Deep Learning for R-3D-YOLOv3 Image Classification and Filtering

Sudhakar Sengan,Subramaniyaswamy Vairavasundaram,Vijayakumar Varadarajan,Logesh Ravi,Priya Velayutham,Indragandhi Vairavasundaram,Ketan Kotecha

doi:10.3390/electronics10243079

Abstract

Statistical reports say that, from 2011 to 2021, more than 11,915 stray animals, such as cats, dogs, goats, cows, etc., and wild animals were wounded in road accidents. Most of the accidents occurred due to negligence and doziness of drivers. These issues can be handled brilliantly using stray and wild animals-vehicle interaction and the pedestrians’ awareness. This paper briefs a detailed forum on GPU-based embedded systems and ODT real-time applications. ML trains machines to recognize images more accurately than humans. This provides a unique and real-time solution using deep-learning real 3D motion-based YOLOv3 (DL-R-3D-YOLOv3) ODT of images on mobility. Besides, it discovers methods for multiple views of flexible objects using 3D reconstruction, especially for stray and wild animals. Computer vision-based IoT devices are also besieged by this DL-R-3D-YOLOv3 model. It seeks solutions by forecasting image filters to find object properties and semantics for object recognition methods leading to closed-loop ODT.

Highlights

The computer vision domain is being conquered by deep learning (DL) techniques in general and convolutional neural networks (CNN)
Computer vision (CV)-based Internet of Things (IoT) devices are besieged by this DL real 3D motion-based YOLOv3 model [2]
We proposed R-3D-YOLOv3, a multi-stage registration process in which an innovative analytical shape model is applied to align scans by resuming the process approximately

Summary

Introduction

The computer vision domain is being conquered by deep learning (DL) techniques in general and convolutional neural networks (CNN). Computer vision (CV) endures extensive research in ODT for domestic appliances, medical imaging, industrial automation, defense, and video surveillance. CV is executed on a highperformance cloud-based system. The application of edge devices is very similar to sensors that serve raw data equal to the cloud. CV-based Internet of Things (IoT) devices are besieged by this DL real 3D motion-based YOLOv3 model [2]. Visual imaging is one of the vital senses of humans, as well as stray and wild animals. Our vision is a source of witness on which we have an unshakable trust. We pick up an object while passing through an environment that represents roadways of smart cities, forests, and any other locations while travelling through the vehicle, but neither probes into mere things on the way or recognizes object faces

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Conclusion