Nearness of Sets in Local Admissible Covers. Theory and Application in Micropalaeontology

Peters, James F.

doi:10.3233/fi-2013-890

Cited by 5 publications

(2 citation statements)

References 21 publications

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“…This motivated us to propose a deep learning-based framework for feature extraction and classification to perfomrm face recognition under facial plastic surgery so as to overcome the limitations of the traditional approachs. The proposed approach makes two major contributions viz ; (i) An intrinsic feature selection method, in which features are automatically extracted and selected using a deep neural network; (ii) Near Set feature selection method [ 27 , 29 – 31 ], in which the features are selected based on nearness measure and tolerance relations. Finally, those features are presented to the classifier, which classifies facial features training vectors into their correct face classes using a feature space approximation.…”

Section: Introductionmentioning

confidence: 99%

Designing face resemblance technique using near set theory under varying facial features

Khedgaonkar¹,

Singh²

2023

Multimed Tools Appl

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Near sets (also called Descriptively Near Sets) classify nonempty sets of objects based on object feature values. The Near Set Theory provides a framework for measuring the similarity of objects based on features that describe them in much the same way humans perceive the similarity of objects. This paper presents a novel approach for face recognition using Near Set Theory that takes into account variations in facial features due to varying facial expressions, and facial plastic surgery. In the proposed work, we demonstrate two-fold usage of Near set theory; firstly, Near Set Theory as a feature selector to select the plastic surgery facial features with the help of tolerance classes, and secondly, Near Set Theory as a recognizer that uses selected prominent intrinsic facial features which are automatically extracted through the deep learning model. Extensive experimentation was performed on various facial datasets such as YALE, PSD, and ASPS. Experimentation demonstrates 93% of accuracy on the YALE face dataset, 98% of accuracy on the PSD dataset, and 98% of accuracy on the ASPS dataset. A detailed comparative analysis of the proposed work of facial resemblance with other state-of-the-art algorithms is presented in this paper. The experimentation results effectively classify face resemblance using Near Set Theory, which has outperformed several state-of-the-art classification approaches.

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Section: Introductionmentioning

confidence: 99%

Designing face resemblance technique using near set theory under varying facial features

Khedgaonkar¹,

Singh²

2023

Multimed Tools Appl

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“…The other notion of near sets have been given by Peters [1,2] where objects, affinities are considered perceptually near to each other, i.e., objects with similar descriptions to some degrees.…”

Section: Introductionmentioning

confidence: 99%

Near Soft Continuous and Near Soft Jp-Continuous Functions H. Tasbozan and N. Bagirmaz

2021

Electronic Journal of Mathematical Analysis and Applications

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Most real life situations need some sort of approximation to fit mathematical models. Pawlak introduced approximations as a means of approximating one set of object with another set of objects using an indiscernibility relation that is based on a comparison between the feature values of objects. Near sets were introduced by Peters where objects with affinities were considered perceptually near to others. Soft set theory was proposed by Molodtsov as a general framework for reasoning about vague concepts. We obtained near soft set by combining two concepts soft set and near sets. Based on a near set topology and near soft open sets, the approximation of a near soft set is proposed to obtain a function called near soft continuous . In this paper, we defined near soft continuous and near soft JP-continuous functions and give some examples about this functions.

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Visibility, Hausdorffness, Algebra and Separation Spaces

Peters

2016

Intelligent Systems Reference Library

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Nearness of Sets in Local Admissible Covers. Theory and Application in Micropalaeontology

Cited by 5 publications

References 21 publications

Designing face resemblance technique using near set theory under varying facial features

Designing face resemblance technique using near set theory under varying facial features

Near Soft Continuous and Near Soft Jp-Continuous Functions H. Tasbozan and N. Bagirmaz

Visibility, Hausdorffness, Algebra and Separation Spaces

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