A novel multimodal framework for automatic recognition of individual cattle based on hybrid features using sparse stacked denoising autoencoder and group sparse representation techniques

Recently, visual animal bio-metrics have attracted much attention for identifying endangered species and animals based on their prominent bio-metric features. This study explores a new possibility of using facial recognition for an inexpensive and user-friendly bio-metric modality to identify cattle...

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Veröffentlicht in:	Multimedia tools and applications Jg. 81; H. 21; S. 31075 - 31106
Hauptverfasser:	Kumar, Santosh, Kumar, Sunil, Shafi, Mehak, Chaube, Mithilesh Kumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2022 Springer Nature B.V
Schlagworte:	Belief networks Cattle Computer Communication Networks Computer Science Data Structures and Information Theory Endangered species Face recognition Feature extraction Multimedia Information Systems Noise reduction Object recognition Representations Special Purpose and Application-Based Systems Visual animal bio-metrics Deep learning SDAE Group sparse representation Muzzle point
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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