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Sharks

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Artificial neural networks and geometric morphometric methods as a means for classification: A case-study using teeth from Carcharhinus sp. (Carcharhinidae).

Journal of morphology
Over the past few decades, geometric morphometric methods have become increasingly popular and powerful tools to describe morphological data while over the same period artificial neural networks have had a similar rise in the classification of specim...

The use of machine learning to detect foraging behaviour in whale sharks: a new tool in conservation.

Journal of fish biology
In this study we present the first attempt at modelling the feeding behaviour of whale sharks using a machine learning analytical method. A total of eight sharks were monitored with tri-axial accelerometers and their foraging behaviours were visually...

Assessment of Machine Learning Models to Identify Port Jackson Shark Behaviours Using Tri-Axial Accelerometers.

Sensors (Basel, Switzerland)
Movement ecology has traditionally focused on the movements of animals over large time scales, but, with advancements in sensor technology, the focus can become increasingly fine scale. Accelerometers are commonly applied to quantify animal behaviour...

Novel use of deep neural networks on photographic identification of epaulette sharks (Hemiscyllium ocellatum) across life stages.

Journal of fish biology
Photographic identification (photo ID) is an established method that is used to count animals and track individuals' movements. This method performs well with some species of elasmobranchs (i.e., sharks, skates, and rays) where individuals have disti...

Intelligence model on sequence-based prediction of PPI using AISSO deep concept with hyperparameter tuning process.

Scientific reports
Protein-protein interaction (PPI) prediction is vital for interpreting biological activities. Even though many diverse sorts of data and machine learning approaches have been employed in PPI prediction, performance still has to be enhanced. As a resu...