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Consequently, any mapping from real world applications into computer applications requires a certain amount of technical background knowledge by the user, where the semantic gap manifests itself. It is a fundamental task of software engineering to close the gap between application specific knowledge and technically doable formalization. For ...
In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to ...
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos.From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
Correspondence is a fundamental problem in computer vision — influential computer vision researcher Takeo Kanade famously once said that the three fundamental problems of computer vision are: “Correspondence, correspondence, and correspondence!” [2] Indeed, correspondence is arguably the key building block in many related applications ...
Semantic intelligence [1] is the ability to gather the necessary information to allow to identify, detect and solve semantic gaps on all level of the organization.. Similar to Operational intelligence or Business Process intelligence, which aims to identify, detect and then optimize business processes, semantic intelligence targets information instead of processes.
In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans.
Semantics describes the processes a computer follows when executing a program in that specific language. This can be done by describing the relationship between the input and output of a program, or giving an explanation of how the program will be executed on a certain platform , thereby creating a model of computation .
The resulting extended semantics of LP is a variation of the standard semantics of Horn clauses and FOL, and is a form of database semantics, [20] which includes the unique name assumption and a form of closed world assumption. These assumptions are much harder to state and reason with explicitly using the standard semantics of FOL.