Animal Face Classification using Dual Deep Convolutional Neural Network

다국어 초록 (Multilingual Abstract)

A practical animal face classification system that classifies animals in image and video data is considered as a pivotal topic in machine learning. In this research, we are proposing a novel method of fully connected dual Deep Convolutional Neural Network (DCNN), which extracts and analyzes image features on a large scale. With the inclusion of the state of the art Batch Normalization layer and Exponential Linear Unit (ELU) layer, our proposed DCNN has gained the capability of analyzing a large amount of dataset as well as extracting more features than before. For this research, we have built our dataset containing ten thousand animal faces of ten animal classes and a dual DCNN. The significance of our network is that it has four sets of convolutional functions that work laterally with each other. We used a relatively small amount of batch size and a large number of iteration to mitigate overfitting during the training session. We have also used image augmentation to vary the shapes of the training images for the better learning process. The results demonstrate that, with an accuracy rate of 92.0%, the proposed DCNN outruns its counterparts while causing less computing costs.

참고문헌 (Reference)

1 K. Simonyan, "Very Deep Convolutional Networks for Large-scale Image Recognition"

2 S. Mouloodi, "Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm" 1-14, 2019

3 Leslie Ching Ow Tiong, "Multimodal Face Biometrics by Using Convolutional Neural Networks" 한국멀티미디어학회 20 (20): 170-178, 2017

4 "Kernel (image processing)"

5 C. Szegedy, "Going Deeper with Convolutions" 1 : 1-9, 2015

6 G. Chen, "Deep Convolutional Neural Network based Species Recognition for Wild Animal Monitoring" 858-862, 2014

7 "Batch Normalization Layer"

8 라파엘, "Anthropomorphic Animal Face Masking using Deep Convolutional Neural Network based Animal Face Classification" 한국멀티미디어학회 22 (22): 558-572, 2019

9 S. Taheri, "Animal classification using facial images with score-level fusion" 12 (12): 679-685, 2018

10 T. Trnovszky, "Animal Recognition System Based on Convolutional Neural Network" 15 (15): 2017

11 A. Krizhevsky, "Advances in Neural Information Processing Systems" 1106-1114, 2012