Peripheral visionPeripheral vision, or indirect vision, is vision as it occurs outside the point of fixation, i.e. away from the center of gaze or, when viewed at large angles, in (or out of) the "corner of one's eye". The vast majority of the area in the visual field is included in the notion of peripheral vision. "Far peripheral" vision refers to the area at the edges of the visual field, "mid-peripheral" vision refers to medium eccentricities, and "near-peripheral", sometimes referred to as "para-central" vision, exists adjacent to the center of gaze.
Fovea centralisThe fovea centralis is a small, central pit composed of closely packed cones in the eye. It is located in the center of the macula lutea of the retina. The fovea is responsible for sharp central vision (also called foveal vision), which is necessary in humans for activities for which visual detail is of primary importance, such as reading and driving. The fovea is surrounded by the parafovea belt and the perifovea outer region.
PerceptionPerception () is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system, which in turn result from physical or chemical stimulation of the sensory system. Vision involves light striking the retina of the eye; smell is mediated by odor molecules; and hearing involves pressure waves.
Visual acuityVisual acuity (VA) commonly refers to the clarity of vision, but technically rates a person's ability to recognize small details with precision. Visual acuity depends on optical and neural factors. Optical factors of the eye influence the sharpness of an image on its retina. Neural factors include the health and functioning of the retina, of the neural pathways to the brain, and of the interpretative faculty of the brain. The most commonly referred-to visual acuity is distance acuity or far acuity (e.g.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Visual perceptionVisual perception is the ability to interpret the surrounding environment through photopic vision (daytime vision), color vision, scotopic vision (night vision), and mesopic vision (twilight vision), using light in the visible spectrum reflected by objects in the environment. This is different from visual acuity, which refers to how clearly a person sees (for example "20/20 vision"). A person can have problems with visual perceptual processing even if they have 20/20 vision.
Neural adaptationNeural adaptation or sensory adaptation is a gradual decrease over time in the responsiveness of the sensory system to a constant stimulus. It is usually experienced as a change in the stimulus. For example, if a hand is rested on a table, the table's surface is immediately felt against the skin. Subsequently, however, the sensation of the table surface against the skin gradually diminishes until it is virtually unnoticeable. The sensory neurons that initially respond are no longer stimulated to respond; this is an example of neural adaptation.
MaculaThe macula (/ˈmakjʊlə/) or macula lutea is an oval-shaped pigmented area in the center of the retina of the human eye and in other animals. The macula in humans has a diameter of around and is subdivided into the umbo, foveola, foveal avascular zone, fovea, parafovea, and perifovea areas. The anatomical macula at a size of is much larger than the clinical macula which, at a size of , corresponds to the anatomical fovea.
Neural networkA neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.
Target audienceA target audience is the intended audience or readership of a publication, advertisement, or other message catered specifically to said intended audience. In marketing and advertising, it is a particular group of consumer within the predetermined target market, identified as the targets or recipients for a particular advertisement or message. Businesses that have a wide target market will focus on a specific target audience for certain messages to send, such as The Body Shops Mother's Day advertisements, which were aimed at the children and spouses of women, rather than the whole market which would have included the women themselves.
