Animal Recognition and Identification Using AI

• Author(s): Dhruv Bisht; Om Tiwari; Dr. Anuj Chandila; Prof. (Dr.) Sanjay Pachauri
• Paper ID: 1712156
• Page: 1433-1434
• Published Date: 20-11-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025

Abstract

This paper introduces Animal Vision, a system based on AI for the automatic detection and recognition of animals using state-of-the-art deep learning techniques. It focuses its study only on approaches and techniques concerning the identification of wildlife without including results related to system performance. This system integrates object detection architectures like YOLOv5, FCOS, and Cascade R-CNN, together with CNN-based frameworks for species classification. These techniques make it possible to analyze camera-trap images automatically, thereby supporting applications on wildlife conservation, ecological monitoring, and surveillance.

Keywords

Artificial Intelligence, Deep Learning, YOLOv5, FCOS, Cascade R-CNN, CNN, Animal Identification

Citations

IRE Journals:
Dhruv Bisht, Om Tiwari, Dr. Anuj Chandila, Prof. (Dr.) Sanjay Pachauri "Animal Recognition and Identification Using AI" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 1433-1434 https://doi.org/10.64388/IREV9I5-1712156

IEEE:
Dhruv Bisht, Om Tiwari, Dr. Anuj Chandila, Prof. (Dr.) Sanjay Pachauri "Animal Recognition and Identification Using AI" Iconic Research And Engineering Journals, 9(5) https://doi.org/10.64388/IREV9I5-1712156