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FaceNet is a facial recognition system developed by Florian Schroff, Dmitry Kalenichenko and James Philbina, a group of researchers affiliated with Google.The system was first presented at the 2015 IEEE Conference on Computer Vision and Pattern Recognition. [1]
Lens can also use images to identify text and can find results from Google Search or translate the text with Google Translate in augmented reality. [9] Lens is also integrated with the Google Photos and Google Assistant apps. [5] The service originally launched as Google Goggles, a previous app that functioned similarly but with less capability.
Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. [1] Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.
The hashing method initially relied on converting images into a black-and-white format, dividing them into squares, and quantifying the shading of the squares, [5] did not employ facial recognition technology, nor could it identify a person or object in the image.
DeepFace systems can identify faces with 97% accuracy, almost the same accuracy as a human in the same position. Facebook's facial recognition is more effective than the FBI's technology, which has 85% accuracy. [9] Google's technology, FaceNet is more successful than DeepFace using the same data sets. FaceNet set a record for accuracy, 99.63%.
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.
The Face Recognition Grand Challenge (FRGC) was a project that aimed to promote and advance face recognition technology to support existing face recognition efforts within the U.S. Government. The project ran from May 2004 to March 2006 and was open to face recognition researchers and developers in companies, academia, and research institutions.
The PNG (Portable Network Graphics) file format was created as a free, open-source alternative to GIF. The PNG file format supports 8-bit (256 colors) paletted images (with optional transparency for all palette colors) and 24-bit truecolor (16 million colors) or 48-bit truecolor with and without alpha channel – while GIF supports only 8-bit ...