Classification of Animal Behaviour Using Deep Learning Models
Damage to crops by animal intrusion is one of the biggest threats to crop yield. People who stay near forest areas face a major issue with animals. The most significant task in deep learning is animal behaviour classification. This article focuses on the classification of distinct animal behaviours...
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| Format: | Article |
| Language: | English |
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Ediciones Universidad de Salamanca
2024-12-01
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| Series: | Advances in Distributed Computing and Artificial Intelligence Journal |
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| Online Access: | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/31638 |
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| author | M. Sowmya M. Balasubramanian K. Vaidehi |
| author_facet | M. Sowmya M. Balasubramanian K. Vaidehi |
| author_sort | M. Sowmya |
| collection | DOAJ |
| description | Damage to crops by animal intrusion is one of the biggest threats to crop yield. People who stay near forest areas face a major issue with animals. The most significant task in deep learning is animal behaviour classification. This article focuses on the classification of distinct animal behaviours such as sitting, standing, eating etc. The proposed system detects animal behaviours in real time using deep learning-based models, namely, convolution neural network and transfer learning. Specifically, 2D-CNN, VGG16 and ResNet50 architectures have been used for classification. 2D-CNN, «VGG-16» and «ResNet50» have been trained on the video frames displaying a range of animal behaviours. The real time behaviour dataset contains 682 images of animals eating, 300 images of animas sitting and 1002 images of animals standing, therefore, there is a total of 1984 images in the training dataset. The experiment shows good accuracy results on the real time dataset, achieving 99.43 % with Resnet50 compared to 2D CNN ,VGG19 and VGG166. |
| format | Article |
| id | doaj-art-a7aeb605b9b94b70b1a859471797013c |
| institution | Kabale University |
| issn | 2255-2863 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Ediciones Universidad de Salamanca |
| record_format | Article |
| series | Advances in Distributed Computing and Artificial Intelligence Journal |
| spelling | doaj-art-a7aeb605b9b94b70b1a859471797013c2025-01-23T11:25:18ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632024-12-0113e31638e3163810.14201/adcaij.3163837119Classification of Animal Behaviour Using Deep Learning ModelsM. Sowmya0M. Balasubramanian1K. Vaidehi2Research Scholar, Department of CSE, Annamalai University, Annamalai Nagar, IndiaAssociate Professor, Department of CSE, Annamalai University, Annamalai Nagar, IndiaAssociate Professor, Department of CSE, Stanley College of Engineering and Technology for Women, Hyderabad, IndiaDamage to crops by animal intrusion is one of the biggest threats to crop yield. People who stay near forest areas face a major issue with animals. The most significant task in deep learning is animal behaviour classification. This article focuses on the classification of distinct animal behaviours such as sitting, standing, eating etc. The proposed system detects animal behaviours in real time using deep learning-based models, namely, convolution neural network and transfer learning. Specifically, 2D-CNN, VGG16 and ResNet50 architectures have been used for classification. 2D-CNN, «VGG-16» and «ResNet50» have been trained on the video frames displaying a range of animal behaviours. The real time behaviour dataset contains 682 images of animals eating, 300 images of animas sitting and 1002 images of animals standing, therefore, there is a total of 1984 images in the training dataset. The experiment shows good accuracy results on the real time dataset, achieving 99.43 % with Resnet50 compared to 2D CNN ,VGG19 and VGG166.https://revistas.usal.es/cinco/index.php/2255-2863/article/view/31638animal image classificationdeep learningcnnvgg16vgg19resnet50 |
| spellingShingle | M. Sowmya M. Balasubramanian K. Vaidehi Classification of Animal Behaviour Using Deep Learning Models Advances in Distributed Computing and Artificial Intelligence Journal animal image classification deep learning cnn vgg16 vgg19 resnet50 |
| title | Classification of Animal Behaviour Using Deep Learning Models |
| title_full | Classification of Animal Behaviour Using Deep Learning Models |
| title_fullStr | Classification of Animal Behaviour Using Deep Learning Models |
| title_full_unstemmed | Classification of Animal Behaviour Using Deep Learning Models |
| title_short | Classification of Animal Behaviour Using Deep Learning Models |
| title_sort | classification of animal behaviour using deep learning models |
| topic | animal image classification deep learning cnn vgg16 vgg19 resnet50 |
| url | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/31638 |
| work_keys_str_mv | AT msowmya classificationofanimalbehaviourusingdeeplearningmodels AT mbalasubramanian classificationofanimalbehaviourusingdeeplearningmodels AT kvaidehi classificationofanimalbehaviourusingdeeplearningmodels |