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  2. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    Examples include upper torsos, pedestrians, and cars. Face detection simply answers two question, 1. are there any human faces in the collected images or video? 2. where is the face located? Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit ...

  3. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    Hugging Face, Inc. is an American company that develops computation tools for building applications using machine learning. It is incorporated under the Delaware General Corporation Law [1] and based in New York City. It is known for its transformers library built for natural language processing applications.

  4. 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.

  5. FaceNet - Wikipedia

    en.wikipedia.org/wiki/FaceNet

    The system uses a deep convolutional neural network to learn a mapping (also called an embedding) from a set of face images to a 128-dimensional Euclidean space, and assesses the similarity between faces based on the square of the Euclidean distance between the images' corresponding normalized vectors in the 128-dimensional Euclidean space.

  6. 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).

  7. Scale-invariant feature transform - Wikipedia

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

    The new approach calculates the interpolated location of the extremum, which substantially improves matching and stability. [2] The interpolation is done using the quadratic Taylor expansion of the Difference-of-Gaussian scale-space function, D ( x , y , σ ) {\displaystyle D\left(x,y,\sigma \right)} with the candidate keypoint as the origin.

  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. Clearview AI - Wikipedia

    en.wikipedia.org/wiki/Clearview_AI

    Clearview AI, Inc. is an American facial recognition company, providing software primarily to law enforcement and other government agencies. [2] The company's algorithm matches faces to a database of more than 20 billion images collected from the Internet, including social media applications. [1]