Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4759208 | Computers and Electronics in Agriculture | 2016 | 11 Pages |
Abstract
The feature selection process used in developing each of the binary classifiers found that features representing the motion intensity and pitch of the cow's head were most important to each of behavior's classification. Whilst a minor performance improvement was obtained using the proposed methodology, it is suggested that further performance improvements could be obtained by increasing the diversity of the classifier's inputs. Diversity could be created by fusing the data of other sensors that can be fitted to the cows i.e. GPS tracking unit, pressure sensor and microphone.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Daniel Smith, Ashfaqur Rahman, Greg J. Bishop-Hurley, James Hills, Sumon Shahriar, David Henry, Richard Rawnsley,