Face recognition using particle swarm optimization based block ICA

Pati, Rasmikanta; Pujari, Arun K.; Gahan, Padmabati

doi:10.1007/s11042-021-10792-5

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…First, in the direction of introducing PSO combined with the original image feature extraction technology, the literature [ 80 ] proposed an ICA image feature extraction algorithm based on PSO. This algorithm introduces the PSO algorithm into the feature extraction process of the traditional ICA algorithm, which is used to optimize the objective function and can quickly find the global optimal solution of the objective function.…”

Section: Swarm Intelligence and Its Application In Image Processingmentioning

confidence: 99%

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

Cao

et al. 2023

Biomimetics

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Image processing technology has always been a hot and difficult topic in the field of artificial intelligence. With the rise and development of machine learning and deep learning methods, swarm intelligence algorithms have become a hot research direction, and combining image processing technology with swarm intelligence algorithms has become a new and effective improvement method. Swarm intelligence algorithm refers to an intelligent computing method formed by simulating the evolutionary laws, behavior characteristics, and thinking patterns of insects, birds, natural phenomena, and other biological populations. It has efficient and parallel global optimization capabilities and strong optimization performance. In this paper, the ant colony algorithm, particle swarm optimization algorithm, sparrow search algorithm, bat algorithm, thimble colony algorithm, and other swarm intelligent optimization algorithms are deeply studied. The model, features, improvement strategies, and application fields of the algorithm in image processing, such as image segmentation, image matching, image classification, image feature extraction, and image edge detection, are comprehensively reviewed. The theoretical research, improvement strategies, and application research of image processing are comprehensively analyzed and compared. Combined with the current literature, the improvement methods of the above algorithms and the comprehensive improvement and application of image processing technology are analyzed and summarized. The representative algorithms of the swarm intelligence algorithm combined with image segmentation technology are extracted for list analysis and summary. Then, the unified framework, common characteristics, different differences of the swarm intelligence algorithm are summarized, existing problems are raised, and finally, the future trend is projected.

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Section: Swarm Intelligence and Its Application In Image Processingmentioning

confidence: 99%

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

Cao

et al. 2023

Biomimetics

View full text Add to dashboard Cite

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Tracking Unauthorized Access Using Machine Learning and PCA for Face Recognition Developments

Păvăloaia

Husac

2022

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In the last two decades there has been obtained tremendous improvements in the field of artificial intelligence (AI) especially in the sector of face/facial recognition (FR). Over the years, the world obtained remarkable progress in the technology that enhanced the face detection techniques use on common PCs and smartphones. Moreover, the steadily progress of programming languages, libraries, frameworks, and tools combined with the great passion of developers and researchers worldwide contribute substantially to open-source AI materials that produced machine learning (ML) algorithms available to any scholar with the will to build the software of tomorrow. The study aims to analyze the specialized literature starting from the first prototype delivered by Cambridge University until the most recent discoveries in FR. The purpose is to identify the most proficient algorithms, and the existing gap in the specialized literature. The research builds a FR application based on simplicity and efficiency of code that facilitates a person’s face detection using a real time photo and validate the access by querying a given database. The paper brings contribution to the field throughout the literature review analysis as well as by the customized code in Phyton, using ML with Principal Component Analysis (PCA), AdaBoost and MySQL for a myriad of application’s development in a variety of domains.

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Face recognition using particle swarm optimization based block ICA

Cited by 2 publications

References 19 publications

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

Tracking Unauthorized Access Using Machine Learning and PCA for Face Recognition Developments

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