Feedforward neural networkA feedforward neural network (FNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. Its flow is uni-directional, meaning that the information in the model flows in only one direction—forward—from the input nodes, through the hidden nodes (if any) and to the output nodes, without any cycles or loops, in contrast to recurrent neural networks, which have a bi-directional flow.
OmmatidiumThe compound eyes of arthropods like insects, crustaceans and millipedes are composed of units called ommatidia (singular: ommatidium). An ommatidium contains a cluster of photoreceptor cells surrounded by support cells and pigment cells. The outer part of the ommatidium is overlaid with a transparent cornea. Each ommatidium is innervated by one axon bundle (usually consisting of 6–9 axons, depending on the number of rhabdomeres) and provides the brain with one picture element.
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.
Object recognition (cognitive science)Visual object recognition refers to the ability to identify the objects in view based on visual input. One important signature of visual object recognition is "object invariance", or the ability to identify objects across changes in the detailed context in which objects are viewed, including changes in illumination, object pose, and background context. Neuropsychological evidence affirms that there are four specific stages identified in the process of object recognition.
Residual neural networkA Residual Neural Network (a.k.a. Residual Network, ResNet) is a deep learning model in which the weight layers learn residual functions with reference to the layer inputs. A Residual Network is a network with skip connections that perform identity mappings, merged with the layer outputs by addition. It behaves like a Highway Network whose gates are opened through strongly positive bias weights. This enables deep learning models with tens or hundreds of layers to train easily and approach better accuracy when going deeper.
Computer simulationComputer simulation is the process of mathematical modelling, performed on a computer, which is designed to predict the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics (computational physics), astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering.
Global North and Global SouthThe concept of Global North and Global South (or North–South divide in a global context) is used to describe a grouping of countries along the lines of socio-economic and political characteristics. The Global South is a term that broadly comprises countries in the regions of Africa, Latin America and the Caribbean, Asia (without Israel, Japan, and South Korea), and Oceania (without Australia and New Zealand), according to the United Nations Conference on Trade and Development (UNCTAD).
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Depth perceptionDepth perception is the ability to perceive distance to objects in the world using the visual system and visual perception. It is a major factor in perceiving the world in three dimensions. Depth perception happens primarily due to stereopsis and accommodation of the eye. Depth sensation is the corresponding term for non-human animals, since although it is known that they can sense the distance of an object, it is not known whether they perceive it in the same way that humans do. Depth perception arises from a variety of depth cues.
Motion perceptionMotion perception is the process of inferring the speed and direction of elements in a scene based on visual, vestibular and proprioceptive inputs. Although this process appears straightforward to most observers, it has proven to be a difficult problem from a computational perspective, and difficult to explain in terms of neural processing. Motion perception is studied by many disciplines, including psychology (i.e. visual perception), neurology, neurophysiology, engineering, and computer science.
