Feature (computer vision)In computer vision and , a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. Other examples of features are related to motion in image sequences, or to shapes defined in terms of curves or boundaries between different image regions.
Ethics of artificial intelligenceThe ethics of artificial intelligence is the branch of the ethics of technology specific to artificially intelligent systems. It is sometimes divided into a concern with the moral behavior of humans as they design, make, use and treat artificially intelligent systems, and a concern with the behavior of machines, in machine ethics. Robot ethics The term "robot ethics" (sometimes "roboethics") refers to the morality of how humans design, construct, use and treat robots. Robot ethics intersect with the ethics of AI.
Hierarchical temporal memoryHierarchical temporal memory (HTM) is a biologically constrained machine intelligence technology developed by Numenta. Originally described in the 2004 book On Intelligence by Jeff Hawkins with Sandra Blakeslee, HTM is primarily used today for anomaly detection in streaming data. The technology is based on neuroscience and the physiology and interaction of pyramidal neurons in the neocortex of the mammalian (in particular, human) brain. At the core of HTM are learning algorithms that can store, learn, infer, and recall high-order sequences.
Expert systemIn artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of artificial intelligence (AI) software.
Lasso (statistics)In statistics and machine learning, lasso (least absolute shrinkage and selection operator; also Lasso or LASSO) is a regression analysis method that performs both variable selection and regularization in order to enhance the prediction accuracy and interpretability of the resulting statistical model. It was originally introduced in geophysics, and later by Robert Tibshirani, who coined the term. Lasso was originally formulated for linear regression models. This simple case reveals a substantial amount about the estimator.
Utility modelA utility model is a patent-like intellectual property right to protect inventions. This type of right is available in many countries but, notably, not in the United States, United Kingdom or Canada. Although a utility model is similar to a patent, it is generally cheaper to obtain and maintain, has a shorter term (generally 6 to 15 years), shorter grant lag, and less stringent patentability requirements. In some countries, it is only available for inventions in certain fields of technology and/or only for products.
DOCSISData Over Cable Service Interface Specification (DOCSIS) is an international telecommunications standard that permits the addition of high-bandwidth data transfer to an existing cable television (CATV) system. It is used by many cable television operators to provide cable Internet access over their existing hybrid fiber-coaxial (HFC) infrastructure. DOCSIS was originally developed by CableLabs and contributing companies, including Arris, BigBand Networks, Broadcom, Cisco, Comcast, Conexant, Correlant, Cox, Harmonic, Intel, Motorola, Netgear, Terayon, Time Warner Cable, and Texas Instruments.
Friendly artificial intelligenceFriendly artificial intelligence (also friendly AI or FAI) is hypothetical artificial general intelligence (AGI) that would have a positive (benign) effect on humanity or at least align with human interests or contribute to fostering the improvement of the human species. It is a part of the ethics of artificial intelligence and is closely related to machine ethics. While machine ethics is concerned with how an artificially intelligent agent should behave, friendly artificial intelligence research is focused on how to practically bring about this behavior and ensuring it is adequately constrained.
Human rightsHuman rights are moral principles or norms for certain standards of human behaviour and are regularly protected in municipal and international law. They are commonly understood as inalienable, fundamental rights "to which a person is inherently entitled simply because she or he is a human being" and which are "inherent in all human beings", regardless of their age, ethnic origin, location, language, religion, ethnicity, or any other status.
Overjustification effectThe overjustification effect occurs when an expected external incentive such as money or prizes decreases a person's intrinsic motivation to perform a task. Overjustification is an explanation for the phenomenon known as motivational "crowding out". The overall effect of offering a reward for a previously unrewarded activity is a shift to extrinsic motivation and the undermining of pre-existing intrinsic motivation.
Key-agreement protocolIn cryptography, a key-agreement protocol is a protocol whereby two or more parties can agree on a cryptographic key in such a way that both influence the outcome. If properly done, this precludes undesired third parties from forcing a key choice on the agreeing parties. Protocols that are useful in practice also do not reveal to any eavesdropping party what key has been agreed upon. Many key exchange systems have one party generate the key, and simply send that key to the other party—the other party has no influence on the key.
Scale-invariant feature transformThe scale-invariant feature transform (SIFT) is a computer vision algorithm to detect, describe, and match local features in images, invented by David Lowe in 1999. Applications include object recognition, robotic mapping and navigation, , 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving. SIFT keypoints of objects are first extracted from a set of reference images and stored in a database.
