Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network
Dairy cow face recognition using Neural Networks has several hurdles. For example, there are only a few instances of each individual. The positions and angles of the individuals in the image fluctuate considerably, the differences between individuals are not apparent, and the number of individuals t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9795017/ |
| _version_ | 1828444037887033344 |
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| author | Feng Xu Jing Gao Xin Pan |
| author_facet | Feng Xu Jing Gao Xin Pan |
| author_sort | Feng Xu |
| collection | DOAJ |
| description | Dairy cow face recognition using Neural Networks has several hurdles. For example, there are only a few instances of each individual. The positions and angles of the individuals in the image fluctuate considerably, the differences between individuals are not apparent, and the number of individuals that the network has not been trained on is enormous, etc. In this paper, an enhanced Siamese Neural Network is used to overcome these barriers. First, a combination of Dense Block (DB) and Capsule Network is employed as a feature extractor to keep the spatial information of features while expanding the feature extraction capabilities of the Convolutional Neural Network. Second, image pairings are processed through the Siamese Neural Network to obtain bivariate features. Finally, image recognition is achieved via the correlation analysis of bivariate features. We conduct comparison experiments with different networks on a small cow face dataset. The experimental results demonstrate that Siamese DB Capsule Network can learn abstract knowledge about distinct individuals and can be extended to unfamiliar cows for zero-shot learning. |
| first_indexed | 2024-12-10T21:37:26Z |
| format | Article |
| id | doaj.art-ec241552cb6e4b94b533e822ac1d398f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-10T21:37:26Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ec241552cb6e4b94b533e822ac1d398f2022-12-22T01:32:36ZengIEEEIEEE Access2169-35362022-01-0110631896319810.1109/ACCESS.2022.31828069795017Cow Face Recognition for a Small Sample Based on Siamese DB Capsule NetworkFeng Xu0https://orcid.org/0000-0001-6786-6202Jing Gao1https://orcid.org/0000-0001-5983-1114Xin Pan2College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, ChinaCollege of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, ChinaCollege of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, ChinaDairy cow face recognition using Neural Networks has several hurdles. For example, there are only a few instances of each individual. The positions and angles of the individuals in the image fluctuate considerably, the differences between individuals are not apparent, and the number of individuals that the network has not been trained on is enormous, etc. In this paper, an enhanced Siamese Neural Network is used to overcome these barriers. First, a combination of Dense Block (DB) and Capsule Network is employed as a feature extractor to keep the spatial information of features while expanding the feature extraction capabilities of the Convolutional Neural Network. Second, image pairings are processed through the Siamese Neural Network to obtain bivariate features. Finally, image recognition is achieved via the correlation analysis of bivariate features. We conduct comparison experiments with different networks on a small cow face dataset. The experimental results demonstrate that Siamese DB Capsule Network can learn abstract knowledge about distinct individuals and can be extended to unfamiliar cows for zero-shot learning.https://ieeexplore.ieee.org/document/9795017/Capsule networkcow face recognitionindividual recognitionone-shot learningPearson correlation coefficientSiamese neural network |
| spellingShingle | Feng Xu Jing Gao Xin Pan Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network IEEE Access Capsule network cow face recognition individual recognition one-shot learning Pearson correlation coefficient Siamese neural network |
| title | Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network |
| title_full | Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network |
| title_fullStr | Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network |
| title_full_unstemmed | Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network |
| title_short | Cow Face Recognition for a Small Sample Based on Siamese DB Capsule Network |
| title_sort | cow face recognition for a small sample based on siamese db capsule network |
| topic | Capsule network cow face recognition individual recognition one-shot learning Pearson correlation coefficient Siamese neural network |
| url | https://ieeexplore.ieee.org/document/9795017/ |
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