Facial recognition system introduced varying technologies to the procedure. Some of the most notable include the following techniques: Some face recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face. For example, an algorithm may analyze the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features are then used to search for other images with matching features. Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face recognition. A probe image is then compared with
Insensitivity to sample size this is an artifact of sample size. Because of the small sample size, the incidence of a certain kind of cancer in small rural counties is more likely to be further from the mean, in one direction or another, than the incidence of the same kind of cancer in much more heavily populated urban counties. Insensitivity to sample size Insensitivity to sample size is a cognitive bias that occurs when people judge the probability of obtaining a sample statistic without respect to the sample size. For example, in one study subjects assigned the same probability to the likelihood of obtaining