Pattern recognition: Advanced development, techniques and application for image retrieval

Khodaskar, Anuja; Ladhake, S. A.

doi:10.1109/cnt.2014.7062728

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…Therefore, FS methods from statistical pattern recognition were employed. These methods, although from a completely different field of science and research, are known to have been successfully applied across vastly different scientific areas, including management (Pudil et al, 2014a;Khodaskar & Ladhake, 2014;Escobar & Morales-Menendez, 2017).…”

Section: Feature Selection Methodology -Daf and Pseudo-kernel Regression Modelmentioning

confidence: 99%

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Pudil

Somol

Mikova

et al. 2021

Business, Management and Economics Engineering

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Purpose – The paper presents the results of the study based on a sample of 358 organisations that focuses on further education and training (FET) of their employees. It specifically investigates which specific educational methods and various characteristics of organisations are associated with their financial performance. Research methodology – The Dependency Aware Feature (DAF) selection method from statistical pattern recognition has been used to identify which of the 37 considered variables are most associated with the profitability indicators (ROA, ROCE, ROS). Findings – The profitability indices are significantly associated with some of the specific methods of FET. Organisations should pay attention particularly to instructing, coaching and mentoring. The results also confirm the importance of talent management for organisations to be successful. Research limitations – The examined sample consists solely of organisations operating in the Czech Republic. Shortly, we plan to extend the selection by including organisations from abroad. Practical implications – The study provides recommendations for HR managers for the goals they should focus on. Organisations should evaluate the impacts of FET; otherwise increasing investments in it may not have an effect. Originality/Value – The originality of the current study lies in using a new methodology based on machine learning and respecting complex mutual relations among variables.

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Section: Feature Selection Methodology -Daf and Pseudo-kernel Regression Modelmentioning

confidence: 99%

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Pudil

Somol

Mikova

et al. 2021

Business, Management and Economics Engineering

View full text Add to dashboard Cite

show abstract

“…These methods are best suited for problems where data can be linearly separable, i.e., if there exists a hyperplane which divides all data points into two separate groups (in two dimensions) or more (in higher dimensions). The classifier chooses the decision boundary to the maximum margin atwix the classes, meaning class points are taken most apart from decision boundaries [11].…”

Section: Support Vector Machine (Svm)mentioning

confidence: 99%

Pattern Recognition in Medical Decision Support and Estimating Redundancy in Clinical Text

Sai,

Thokala

2024

Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security,

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Feature sets selected for multidimensional pattern classification are estimated using a novel criterion. The priority of features for each class is generally optimized to maximize relevancy and minimize redundancy between each class. While mutual information can be used to estimate relevancy information, redundancy information cannot be estimated since its dynamic ambit is determined by feature and class. In addition to assisting in adjust of changing patterns, support vector machines are helpful in classifying normal and abnormal patterns. In pattern matching, Random Forest Logic's pattern recognition algorithm lends itself easily to pattern matching algorithms. An algorithm for evaluating the classification performance of health care medical data is proposed. A variety of experimental results confirm that the proffered technique is more veracious than conventional algorithms relating to the classification of accuracy when the number of selected features is varied.

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“…In this context, the texture of objects plays a prominent role, as it can be easily highlighted by our interpretation of black-and-white images. In addition, colors provide additional details to complement our inferences about the objects in question, serving as a more detailed classifier (KHODASKAR and LADHAKE, 2014).…”

Section: Image Analysismentioning

confidence: 99%

Optimization of resistance to gastrointestinal nematodes in Santa Inês sheep: a genomic selection, machine learning and image analysis approach

Januário

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Otimização da resistência a nematódeos gastrointestinais em ovinos Santa Inês: uma abordagem de seleção genômica, machine learning e análise de imagens Ribeirão Preto 2023 LUARA AFONSO DE FREITAS JANUÁRIO Otimização da resistência a nematódeos gastrointestinais em ovinos Santa Inês: uma abordagem de seleção genômica, machine learning e análise de imagens Tese apresentada ao programa de Pós-graduação

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Pattern recognition: Advanced development, techniques and application for image retrieval

Cited by 11 publications

References 13 publications

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Further Education, Its Methods and Selected Characteristics of Organisations: An Empirical Study of Their Association With Organisations Profitability

Pattern Recognition in Medical Decision Support and Estimating Redundancy in Clinical Text

Optimization of resistance to gastrointestinal nematodes in Santa Inês sheep: a genomic selection, machine learning and image analysis approach

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