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Experiments on blue jays suggest they form a search image for certain prey.. Visual predators may form what is termed a search image of certain prey.. Predators need not locate their host directly: Kestrels, for instance, are able to detect the faeces and urine of their prey (which reflect ultraviolet), allowing them to identify areas where there are large numbers of voles, for example.
This is a behavioral form of detection avoidance called crypsis used by animals to either avoid predation or to enhance prey hunting. Predation risk has long been recognized as critical in shaping behavioral decisions. For example, this predation risk is of prime importance in determining the time of evening emergence in echolocating bats.
The neural basis of prey detection, recognition, and orientation was studied in depth by Jörg-Peter Ewert in a series of experiments that made the toad visual system a model system in neuroethology (neural basis of natural behavior). He began by observing the natural prey catching behavior of the common European toad (Bufo bufo).
A cheetah exhibiting pursuit predation. Pursuit predation is a form of predation in which predators actively give chase to their prey, either solitarily or as a group.It is an alternate predation strategy to ambush predation — pursuit predators rely on superior speed, endurance and/or teamwork to seize the prey, while ambush predators use concealment, luring, exploiting of surroundings and ...
Feature learning is intended to result in faster training or better performance in task-specific settings than if the data was input directly (compare transfer learning). [1] In machine learning (ML), feature learning or representation learning [2] is a set of techniques that allow a system to automatically discover the representations needed ...
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent patterns.
Supervised anomaly detection techniques require a data set that has been labeled as "normal" and "abnormal" and involves training a classifier. However, this approach is rarely used in anomaly detection due to the general unavailability of labelled data and the inherent unbalanced nature of the classes.