Iridescence impairs object recognition in bumblebees
نویسندگان
چکیده
منابع مشابه
Disruptive camouflage impairs object recognition.
Whether hiding from predators, or avoiding battlefield casualties, camouflage is widely employed to prevent detection. Disruptive coloration is a seemingly well-known camouflage mechanism proposed to function by breaking up an object's salient features (for example their characteristic outline), rendering objects more difficult to recognize. However, while a wide range of animals are thought to...
متن کاملSleep deprivation impairs object recognition in mice.
Many studies in animals and humans suggest that sleep facilitates learning, memory consolidation, and retrieval. Moreover, sleep deprivation (SD) incurred after learning, impaired memory in humans, mice, rats, and hamsters. We investigated the importance of sleep and its timing in an object recognition task in OF1 mice subjected to 6h SD either immediately after the acquisition phase (0-6 SD) o...
متن کاملFlower Iridescence Increases Object Detection in the Insect Visual System without Compromising Object Identity
Iridescence is a form of structural coloration, produced by a range of structures, in which hue is dependent on viewing angle [1-4]. One of these structures, the diffraction grating, is found both in animals (for example, beetles [2]) and in plants (on the petals of some animal pollinated flowers [5]). The behavioral impacts of floral iridescence and its potential ecological significance are un...
متن کاملBreaking object correspondence across saccades impairs object recognition: The role of color and luminance.
Rapid saccadic eye movements bring the foveal region of the eye's retina onto objects for high-acuity vision. Saccades change the location and resolution of objects' retinal images. To perceive objects as visually stable across saccades, correspondence between the objects before and after the saccade must be established. We have previously shown that breaking object correspondence across the sa...
متن کاملObject Recognition based on Local Steering Kernel and SVM
The proposed method is to recognize objects based on application of Local Steering Kernels (LSK) as Descriptors to the image patches. In order to represent the local properties of the images, patch is to be extracted where the variations occur in an image. To find the interest point, Wavelet based Salient Point detector is used. Local Steering Kernel is then applied to the resultant pixels, in ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientific Reports
سال: 2018
ISSN: 2045-2322
DOI: 10.1038/s41598-018-26571-6