Name
Abstract | ||
|---|---|---|
•Face recognition for humans is a well-studied and proven biometric.•Precision agriculture requires individual animals to be identified reliably.•Current methods e.g. RFID have shortcomings (range, distressing to fit).•We adapt approaches from human literature to on farm pig-face recognition.•Accuracy of 96.7% is achieved on 1553 images of 10 pigs using our own CNN. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compind.2018.02.016 | Computers in Industry |
Keywords | Field | DocType |
Pig face recognition,Deep learning,Convolutional neural network,Biometrics | Facial recognition system,Convolutional neural network,Control engineering,Artificial intelligence,Biometrics,Engineering,Deep learning,Machine learning | Journal |
Volume | ISSN | Citations |
98 | 0166-3615 | 9 |
PageRank | References | Authors |
0.58 | 10 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark F. Hansen | 1 | 69 | 5.27 |
| Melvyn L. Smith | 2 | 194 | 22.20 |
| Lyndon N. Smith | 3 | 117 | 12.58 |
| Michael G. Salter | 4 | 9 | 0.58 |
| Emma M. Baxter | 5 | 9 | 0.58 |
| Marianne Farish | 6 | 9 | 0.58 |
| Grieve, B. | 7 | 11 | 2.69 |