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
Henneman's size principle in this experiment. Experiments were done on 1- to 7-day-old Wistar rats and 20- to 30-day-old Wistar rats as well. The 1- to 7-day-old Wistar rats were selected because early after birth, the rats show an increase in cell size. In 20- to 30-day-old Wistar rats, the physiological and anatomical features of oculomotor nucleus motor neurons remain unchanged. Rat oculomotor nucleus motor neurons were intracellularly labelled and tested using electrophysical properties. The size principle applies to the recruitment order in neonatal motor neurons and also in the adult oculomotor nucleus. The increase in size of motor neurons led to a