• R Indumathi

In this paper, issues related to the development of an effective and efficient animal detection, classification, and tracking system are addressed. Successful attempts towards the development of algorithmic models for animal segmentation, animal detection, classification, and tracking are made. To support the effective classification of animals, we propose two different methods to segment an animal from its background. Evaluation of the proposed animal segmentation algorithm is carried out by the use of region-based performance measures. We also provide a classification model based on several classifiers and features. In addition, we offer a method to identify animals in both photos and videos using a deep learning approach. The various characteristics, including as colour, Gabor, and LBP, are retrieved from the segmented animal images.Initially, features are extracted from images/frames using AlexNet pre-trained Probabilistic neural network. Lat, the extracted features are fed into a multi-class Probabilistic neural network classifier for classification.

Animal recognition system,CNN,SVM, PCA,LBP

"AnimalDetection in Farms Using Deep Neural Networks in Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 2, page no.c15-c18, February-2023, Available :http://www.jetir.org/papers/JETIR2302203.pdf

"AnimalDetection in Farms Using Deep Neural Networks in Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 2, page no. ppc15-c18, February-2023, Available at : http://www.jetir.org/papers/JETIR2302203.pdf