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  2. Viola–Jones object detection framework - Wikipedia

    en.wikipedia.org/wiki/Viola–Jones_object...

    Our task is to make a binary decision: whether it is a photo of a standardized face (frontal, well-lit, etc) or not. Viola–Jones is essentially a boosted feature learning algorithm, trained by running a modified AdaBoost algorithm on Haar feature classifiers to find a sequence of classifiers ,,...,. Haar feature classifiers are crude, but ...

  3. Local binary patterns - Wikipedia

    en.wikipedia.org/wiki/Local_binary_patterns

    LBPLibrary is a collection of eleven Local Binary Patterns (LBP) algorithms developed for background subtraction problem. The algorithms were implemented in C++ based on OpenCV. A CMake file is provided and the library is compatible with Windows, Linux and Mac OS X. The library was tested successfully with OpenCV 2.4.10.

  4. FaceNet - Wikipedia

    en.wikipedia.org/wiki/FaceNet

    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]

  5. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. [3] A reliable face-detection approach based on the genetic algorithm and the eigen-face [4] technique:

  6. Eigenface - Wikipedia

    en.wikipedia.org/wiki/Eigenface

    The technique used in creating eigenfaces and using them for recognition is also used outside of face recognition: handwriting recognition, lip reading, voice recognition, sign language/hand gestures interpretation and medical imaging analysis. Therefore, some do not use the term eigenface, but prefer to use 'eigenimage'.

  7. Object detection - Wikipedia

    en.wikipedia.org/wiki/Object_detection

    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]

  8. Facial recognition system - Wikipedia

    en.wikipedia.org/wiki/Facial_recognition_system

    Facial recognition algorithms can help in diagnosing some diseases using specific features on the nose, cheeks and other part of the human face. [75] Relying on developed data sets, machine learning has been used to identify genetic abnormalities just based on facial dimensions. [76] FRT has also been used to verify patients before surgery ...

  9. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...