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Instance segmentation is an approach that identifies, for every pixel, the specific belonging instance of the object. It detects each distinct object of interest in the image. [19] For example, when each person in a figure is segmented as an individual object. Panoptic segmentation combines both semantic and instance segmentation. Like semantic ...
The random walker algorithm is a segmentation algorithm solving the combinatorial Dirichlet problem, adapted to image segmentation by L. Grady in 2006. [16] In 2011, C. Couprie et al. proved that when the power of the weights of the graph converge toward infinity, the cut minimizing the random walker energy is a cut by maximum spanning forest. [17]
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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.
A semantic data model in software engineering has various meanings: It is a conceptual data model in which semantic information is included. This means that the model describes the meaning of its instances. Such a semantic data model is an abstraction that defines how the stored symbols (the instance data) relate to the real world. [1]
Semantic change has attracted academic discussions since ancient times, although the first major works emerged in the 19th century with Reisig (1839), Paul (1880), and Darmesteter (1887). [4] Studies beyond the analysis of single words have been started with the word-field analyses of Trier (1931) , who claimed that every semantic change of a ...
Market segmentation is a process, in which groups of buyers within a market are divided and profiled according to a range of variables, which determine the market characteristics and tendencies. [2] The S-T-P framework implements market segmentation in three steps: Segmenting means identifying and classifying consumers into categories called ...
The practical significance of semantic interoperability has been measured by several studies that estimate the cost (in lost efficiency) due to lack of semantic interoperability. One study, [ 4 ] focusing on the lost efficiency in the communication of healthcare information, estimated that US$77.8 billion per year could be saved by implementing ...