[PDF] Top 20 Review on outlier tolerant data processing with applications

... the outlier-tolerant estimation of parameters (Dose and Linden, 1999) as well as bounded influence identification, received attention and cited by the academic ...(2009), outlier-Tolerant ... See full document

... big data on corporate ...big data capital and ...big data resides in the close complementarily between big data IT investment and labour ...reviewed applications applied to transfer ... See full document

... their applications in MEMS as thin films by categorizing the known materials in 3 types namely Naturally Occurring Materials, Piezoelectric Ceramics and Piezoelectric ... See full document

... in processing and preserving of meat ...in processing food and misfortunate discernment of new process discipline (ultrasound) by food professionals are contributors to the reluctant utilization of ... See full document

... 2D data (observations) with the 3D representation of these models, or their projection on the camera coordinates (pose estimation ...spatio-temporal processing, where two general directions have been ...the ... See full document

... image processing the field of computer science, digital image processing and so on the use of computer is major and the computer algorithm to perform the given tasks the cost of the processing is ... See full document

... algorithms outlier cluster is establish which is additional amalgamated with other clusters depending upon compromise ...Various outlier clusters which are not going to combine with any other subspace ... See full document

... Big data is the term used to describe huge datasets having the “4 V” definition: volume, variety, velocity and value ...biometrics data, ...of data or redundancy to protect against the frequent media ... See full document

... Abstract - Despite the advances in hardware for hand-held mobile devices, resource-intensive applications (e.g., video and image storage and process or map-reduce type) still stay off bounds since they need ... See full document

... of data. Outlier represents extreme or irregular entries in ...dataset. Outlier detection is applicable in variety of domains such as fraud detection occurred in insurance sector, bank transaction, ... See full document

... colossal data i.e. big data needs new architecture, analytics and techniques to extract valuable information from the data’s ...big data with traditional desktop applications and database ... See full document

... of data has been observed in recent years being a key factor of the Big Data ...Big Data can be defined as high volume, velocity and variety of data that require a new high- performance ...big ... See full document

... query processing, throughput replicating data at several sites is a powerful mechanism which can provide fault ...Different data ownership models are proposed [4], which specifies various mechanisms ... See full document

... in data mining. Outlier detection as a branch of data mining has many important applications and deserves more attention from data mining ...our review of existing outlier ... See full document

... Big Data and business analytics for a wide range of tasks including fraud detection (Phua et ...transaction processing (Dash & Ng, ...harvesting data from social ...credit applications in ... See full document

... in outlier detection. We would like to discuss different method of outlier detection which can be differentiating based on: classic outlier technique based on real time dataset and spatial ... See full document

... Telemetry data flow from sensors fixed in spacecraft are paramount information resources to judge and to diagnose the status of spacecraft in orbit and substantial of them flow can be expressed as ... See full document

... Statistical outlier detection techniques are essentially model- based techniques; ...the data, and the data instances are evaluated with respect to how well they fit the model ...a data ... See full document

... plemented outlier detection algorithms inherit from a base class with the same interface: (i) fit processes the train data and computes the necessary statistics; (ii) decision function generates raw ... See full document

... for processing of low quality trajectory data to achieve high ...of outlier and after removing of outlier for accuracy and Silhouette are presented in figure 5, 6, 7, and 8 ...after ... See full document