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Similarity learning is closely related to distance metric learning.Metric learning is the task of learning a distance function over objects. A metric or distance function has to obey four axioms: non-negativity, identity of indiscernibles, symmetry and subadditivity (or the triangle inequality).
Any human face can be considered to be a combination of these standard faces. For example, one's face might be composed of the average face plus 10% from eigenface 1, 55% from eigenface 2, and even −3% from eigenface 3. Remarkably, it does not take many eigenfaces combined together to achieve a fair approximation of most faces.
The input is an RGB image of the face, scaled to resolution , and the output is a real vector of dimension 4096, being the feature vector of the face image. In the 2014 paper, [ 13 ] an additional fully connected layer is added at the end to classify the face image into one of 4030 possible persons that the network had seen during training time.
Brunswik's lens model is a conceptual framework for describing and studying how people make judgments. For example, a person judging the size of a distant object, physicians assessing the severity of disease, investors judging the quality of stocks, weather forecasters predicting tomorrow's weather and personnel officers rating job candidates all face similar tasks.
A Siamese neural network (sometimes called a twin neural network) is an artificial neural network that uses the same weights while working in tandem on two different input vectors to compute comparable output vectors.
Holistic methods are pre-programmed with statistical information on face shape and landmark location coefficients. The classic holistic method is the active appearance model (AAM) introduced in 1998. [3] Since then there has been a number of extensions and improvements to the method.
SimRank is a general similarity measure, based on a simple and intuitive graph-theoretic model.SimRank is applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects.
The Automated Similarity Judgment Program (ASJP) is a collaborative project applying computational approaches to comparative linguistics using a database of word lists. The database is open access and consists of 40-item basic-vocabulary lists for well over half of the world's languages. [ 1 ]