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The application of deep learning to pattern recognition reflects that human firstly takes as input the pixels of an object projected onto the retina and then detects the edges of the object, recognizes the parts of it, and finally forms the high-level abstract concept of the object [70], as shown in Fig. 7a.
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A system, based on the proposed architecture, was implemented with a collision detector, a scene classifier and a object recognized.
One solution for this problem is that for the points which recognize as a background model pixels, updating carry out with low forgetting coefficient and in the point which moving object recognize, updating carry out with high forgetting coefficient [21].
Each hieroglyphic word both represented a specific object and embodied the essence of that object, recognizing it as divinely made and belonging within the greater cosmos.
Thanks to the recorded observations of Far Eastern and Middle Eastern astronomers of 1054, Crab Nebula became the first astronomical object recognized as being connected to a supernova explosion.
In particular, must the detected features be combined into individual "parts" that must in turn be combined before the object is identified, or is the whole object recognized in one fell swoop? [6].
The aim of the present study is to determine whether human being is able to recognize object instantaneously using peripheral vision without saccadic eye movement, and if so, how large is the field of attention (FA) for instantaneous object recognizing and how is recognizing accuracy distributed over the field.
Our automated cell analysis tool is a method for extracting data from micrographs; it records all morphological and DNA content data from every object recognized from the phase contrast image.
Categorial refinement consists in adding, subtracting, or reconceptualizing the basic objects recognized in the image, e.g., worrying about whether persons are best thought of in hylomorphic or dualistic categories or how things differ from persons.
We also used the MetaCore Analytical Suite to perform the transcription factor and the pathway and toxicity process analysis based on network objects recognized by MetaCore.
Image segmentation is necessary for multiple purposes; for example, counting objects, measuring the two-dimensional (or three-dimensional) distribution of the objects, measuring the shape or appearance of individual objects, recognizing the individual objects, localizing objects for tracking, removing unnecessary regions, etc.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com