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  2. FaceNet - Wikipedia

    en.wikipedia.org/wiki/FaceNet

    The system uses the triplet loss function as its cost function and introduced a new online triplet mining method. The system achieved an accuracy of 99.63%, which is the highest score to date on the Labeled Faces in the Wild dataset using the unrestricted with labeled outside data protocol.

  3. Face Recognition Vendor Test - Wikipedia

    en.wikipedia.org/wiki/Face_Recognition_Vendor_Test

    FRVT Ongoing now has roughly 200 face recognition algorithms and tests against at least six collections of photographs [5] with multiple photographs of more than 8 million people. The best algorithms for 1:1 verification gives False Non Match Rates of 0.0003 at False Match Rates of 0.0001 on high quality visa images. [6] Additional programs:

  4. Speeded up robust features - Wikipedia

    en.wikipedia.org/wiki/Speeded_up_robust_features

    Accordingly, the scale space is analyzed by up-scaling the filter size rather than iteratively reducing the image size. The output of the above 9×9 filter is considered as the initial scale layer at scale s =1.2 (corresponding to Gaussian derivatives with σ = 1.2).

  5. Facial recognition system - Wikipedia

    en.wikipedia.org/wiki/Facial_recognition_system

    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.

  6. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    The hash table is searched to identify all clusters of at least 3 entries in a bin, and the bins are sorted into decreasing order of size. Each of the SIFT keypoints specifies 2D location, scale, and orientation, and each matched keypoint in the database has a record of its parameters relative to the training image in which it was found.

  7. GitHub Copilot - Wikipedia

    en.wikipedia.org/wiki/GitHub_Copilot

    [2] [12] GitHub reports that Copilot’s autocomplete feature is accurate roughly half of the time; with some Python function header code, for example, Copilot correctly autocompleted the rest of the function body code 43% of the time on the first try and 57% of the time after ten attempts.

  8. Template matching - Wikipedia

    en.wikipedia.org/wiki/Template_matching

    Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [ 2 ] navigation of mobile robots , [ 3 ] or edge detection in images.

  9. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    With the availability of large amounts of DNA data, matching of nucleotide sequences has become an important application. [1] Approximate matching is also used in spam filtering. [5] Record linkage is a common application where records from two disparate databases are matched. String matching cannot be used for most binary data, such as images ...