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LibreLogo is an integrated development environment (IDE) for computer programming in the programming language Python, which works like the language Logo using interactive vector turtle graphics. Its final output is a vector graphics rendition within the LibreOffice suite. It can be used for education and desktop publishing.
Turtle graphics are often associated with the Logo programming language. [2] Seymour Papert added support for turtle graphics to Logo in the late 1960s to support his version of the turtle robot, a simple robot controlled from the user's workstation that is designed to carry out the drawing functions assigned to it using a small retractable pen set into or attached to the robot's body.
Logo's most-known feature is the turtle (derived originally from a robot of the same name), [5] an on-screen "cursor" that shows output from commands for movement and small retractable pen, together producing line graphics. It has traditionally been displayed either as a triangle or a turtle icon (though it can be represented by any icon).
The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. It was developed by John F. Canny in 1986. Canny also produced a computational theory of edge detection explaining why the technique works.
PGF/TikZ is a pair of languages for producing vector graphics (e.g., technical illustrations and drawings) from a geometric/algebraic description, with standard features including the drawing of points, lines, arrows, paths, circles, ellipses and polygons.
A micrograph of the corner of the photosensor array of a webcam digital camera Image sensor (upper left) on the motherboard of a Nikon Coolpix L2 6 MP. The two main types of digital image sensors are the charge-coupled device (CCD) and the active-pixel sensor (CMOS sensor), fabricated in complementary MOS (CMOS) or N-type MOS (NMOS or Live MOS) technologies.
Attitude control (spacecraft): Horizon sensor, Earth sensor, Moon sensor, Satellite Sensor, Sun sensor; Catadioptric sensor; Chemoreceptor; Compressive sensing; Cryogenic particle detectors; Dew warning; Diffusion tensor imaging; Digital holography; Electronic tongue; Fine Guidance Sensor; Flat panel detector; Functional magnetic resonance ...
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]