Image classification using hybrid data mining algorithms - a review

Thamilselvan, P; Sathiaseelan, J. G. R.

doi:10.1109/iciiecs.2015.7192922

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…This helps overcome the limitation of one specific method with another one. To address face analysis tasks, data-mining methods are used in [113]. Similarly, gender recognition is explored in [114] through face segmentation.…”

Section: Hybrid Methodsmentioning

confidence: 99%

Face Image Analysis Using Machine Learning: A Survey on Recent Trends and Applications

Ṣiddiqi

Khan

et al. 2022

Electronics

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Human face image analysis using machine learning is an important element in computer vision. The human face image conveys information such as age, gender, identity, emotion, race, and attractiveness to both human and computer systems. Over the last ten years, face analysis methods using machine learning have received immense attention due to their diverse applications in various tasks. Although several methods have been reported in the last ten years, face image analysis still represents a complicated challenge, particularly for images obtained from ’in the wild’ conditions. This survey paper presents a comprehensive review focusing on methods in both controlled and uncontrolled conditions. Our work illustrates both merits and demerits of each method previously proposed, starting from seminal works on face image analysis and ending with the latest ideas exploiting deep learning frameworks. We show a comparison of the performance of the previous methods on standard datasets and also present some promising future directions on the topic.

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Section: Hybrid Methodsmentioning

confidence: 99%

Face Image Analysis Using Machine Learning: A Survey on Recent Trends and Applications

Ṣiddiqi

Khan

et al. 2022

Electronics

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“…Some of traditional database processing techniques are being replaced with data mining techniques dedicated to various applications (Mocanu et al, 2014, Arrais de Freitas et al, 2016. Image mining is based on standard data mining methods (Thamilselvan & Sathiaseelan, 2015). The textual descriptions are not used for image mining and processing.…”

Section: Introductionmentioning

confidence: 99%

Geographic Image Mining

Boicea¹,

Rădulescu²,

Truică³

et al. 2016

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ABSTRACT:Image segmentation is a branch of the image processing domain which involves partitioning the image into multiple segments referred to as sets of pixels. The segmentation purpose is to change the representation of an image into a form that is analyzed easier and less processed in order to extract information based on the colors in the image. This paper shows how we can determine statistics on the relief by processing the images that represent geographic maps through Data Mining algorithms. The important aspects of this type of mining are also described in this study. A dedicated application is used for data processing.

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