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The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008. The second major release of the OpenCV was in October 2009.
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]
DBeaver 3.x announced support of NoSQL databases (Cassandra and MongoDB in the initial version). Since then DBeaver was divided on Community and Enterprise editions. Enterprise Edition has support of NoSQL databases, persistent query manager and a few other enterprise-level features.
Latest release year License Online Windows Mac OS X Linux BSD Android iOS Programming language SDK? Languages Fonts Output Formats Notes ABBYY FineReader: 1989: 16: 2022: Proprietary: Yes: Yes: Yes: No: Yes Yes Yes: C/C++: Yes: 192 [1] All fonts: DOC, DOCX, XLS, XLSX, PPTX, RTF, PDF, HTML, CSV, TXT, ODT, DjVu, EPUB, FB2 [2] ABBYY also supplies ...
Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces.
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos.From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
On average only 0.01% of all sub-windows are positive (faces) Equal computation time is spent on all sub-windows; Must spend most time only on potentially positive sub-windows. A simple 2-feature classifier can achieve almost 100% detection rate with 50% FP rate. That classifier can act as a 1st layer of a series to filter out most negative windows
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