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Paper Title

AI For Wild Life Conservation Wild-Fire detection using YOLOv5 Model

Article Identifiers

Registration ID: IJNRD_218568

Published ID: IJNRD2404614

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Keywords

YOLO, YOLOv5.

Abstract

This article discuss about the usage of artificial intelligence in the conserving wild life via detecting the wild fire occurrence using improved version of YOLO model.The YOLOv5 deep learning model for fire detection is investigated in this work. Rapid fire and smoke identification is made possible by the framework's efficient analysis of photos at a resolution of 416x416 pixels using a single neural network. We study how well YOLOv5 detects items that resemble fire in a variety of settings, such as indoor and outdoor spaces, different types of lighting, and even small-scale fires. The suggested approach's potential for real-time fire detection applications ,which also highlights its excellent balance of speed and accuracy.

How To Cite (APA)

Paidi Hemanthi Naidu & Sonali Kapoor (April-2024). AI For Wild Life Conservation Wild-Fire detection using YOLOv5 Model. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), g144-g147. https://ijnrd.org/papers/IJNRD2404614.pdf

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Other Publication Details

Paper Reg. ID: IJNRD_218568

Published Paper Id: IJNRD2404614

Downloads: 000122256

Research Area: Engineering

Author Type: Indian Author

Country: Mohali, Punjab, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404614.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404614

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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Call For Paper - Volume 10 | Issue 12 | December 2025

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Paper Submission Open For: December 2025

Current Issue: Volume 10 | Issue 12 | December 2025

Impact Factor: 8.76

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