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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Mehrnejad, M. Albu, A.B. Capson, D. Hoeberechts, M. | 
| Copyright Year | 2013 | 
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, BC, Canada (Mehrnejad, M.; Albu, A.B.; Capson, D.) || NEPTUNE Canada, Victoria, BC, Canada (Hoeberechts, M.) | 
| Abstract | Cabled observatory video data are a rich source of information for marine biologists. However, the large amount of recorded video creates a “big data” problem, which calls for automated detection techniques for sea life. Most of the related research has addressed detection based on animal motion. We propose a novel method for the detection of stationary animals, more precisely for crabs. Our approach integrates shape and color information for the automatic detection of crab and non-crab image patches. With these patches we train a feed-forward neural network, which is further used for classifying image patches into crab and non-crab classes. The experimental evaluation shows very promising results. | 
| Sponsorship | IEEE Oceanic Eng. Soc. | 
| Starting Page | 1 | 
| Ending Page | 5 | 
| File Size | 1235482 | 
| Page Count | 5 | 
| File Format | |
| ISBN | 9780933957404 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 2013-09-23 | 
| Publisher Place | USA | 
| Access Restriction | Subscribed | 
| Rights Holder | MTS | 
| Subject Keyword | Image color analysis Histograms Neural networks Shape Animals Image edge detection Training | 
| Content Type | Text | 
| Resource Type | Article | 
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