A novel integrated knowledge support system based on ontology learning: Model specification and a case study

Gil, Richard; Martín-Bautista, María J.

doi:10.1016/j.knosys.2012.07.007

Cited by 23 publications

(15 citation statements)

References 51 publications

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“…The use of formalism for knowledge representation and reasoning for solution of complex problems improves accuracy, recall, and increments speed of these methods. Under controlled conditions, they provide good results, but often they are sensitive to rotation and scaling as well as requiring a structured environment [10,19,20].…”

Section: Modern Techniques For Qr Code Detection and Recognitionmentioning

confidence: 99%

Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments

López-Rincón

Starostenko

Alarcón-Aquino

et al. 2017

Journal of Electrical and Computer Engineering

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Quick Response QR barcode detection in nonarbitrary environment is still a challenging task despite many existing applications for finding 2D symbols. The main disadvantage of recent applications for QR code detection is a low performance for rotated and distorted single or multiple symbols in images with variable illumination and presence of noise. In this paper, a particular solution for QR code detection in uncontrolled environments is presented. The proposal consists in recognizing geometrical features of QR code using a binary large object-(BLOB-) based algorithm with subsequent iterative filtering QR symbol position detection patterns that do not require complex processing and training of classifiers frequently used for these purposes. The high precision and speed are achieved by adaptive threshold binarization of integral images. In contrast to well-known scanners, which fail to detect QR code with medium to strong blurring, significant nonuniform illumination, considerable symbol deformations, and noising, the proposed technique provides high recognition rate of 80%-100% with a speed compatible to real-time applications. In particular, speed varies from 200 ms to 800 ms per single or multiple QR code detected simultaneously in images with resolution from 640 × 480 to 4080 × 2720, respectively.

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Section: Modern Techniques For Qr Code Detection and Recognitionmentioning

confidence: 99%

Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments

López-Rincón

Starostenko

Alarcón-Aquino

et al. 2017

Journal of Electrical and Computer Engineering

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“…Precisely, an updated characterization and classification of the main KSS's profiles as KMS implementations can be found in our previous work in Gil and Martin-Bautista (2012). This cited classification considers KSS applications such as Traditional systems and Intelligent Systems.…”

Section: Ontology-based Kms Implementationsmentioning

confidence: 99%

A novel process-based KMS success framework empowered by ontology learning technology

Herrera

Martín-Bautista

2015

Engineering Applications of Artificial Intelligence

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“…J. Gil. [8] has proposed a novel updating algorithm based on iterative learning strategy for delayed coking unit (DCU), which contains both continuous and discrete characteristics. Daily DCU operations under different conditions are modelled by a belief rule-base (BRB), which is then, updated using iterative learning methodology, based on a novel statistical utility for every belief rule.…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing Stock Market Data Using Clustering Algorithm

Suganthi¹,

Kamalakannan²

2015

IJFCC

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Abstract-In order to analyze the various sectors of the stocks in stock market field, need to use machine learning algorithms to determine the particular sectors of the stocks in intraday trade. In this paper, we compared different types of clustering algorithm with the help of data mining tool WEKA. This paper will demonstrate the strength and accuracy of each algorithm for clustering in terms of performance, efficiency and time complexity required.

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A novel integrated knowledge support system based on ontology learning: Model specification and a case study

Cited by 23 publications

References 51 publications

Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments

Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments

A novel process-based KMS success framework empowered by ontology learning technology

Analyzing Stock Market Data Using Clustering Algorithm

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