Image retrieval based on fireworks algorithm optimizing convolutional neural network

Wang, Chunzhi; Pan, Wei‐Ping; Yan, Lingyu; Zhou, Fangyu; Cai, Wencheng

doi:10.1109/idaacs-sws.2018.8525760

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…e artificial bee colony algorithm was used for robot path planning [20], and the Cuckoo algorithm was used in image segmentation [21]. e fireworks algorithm was used in image retrieval [22]. Compared with other meta-heuristic algorithms, the fireworks algorithm shows excellent performance in optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Color Image Feature Matching Method Based on the Improved Firework Algorithm

Liu

Zhu

Wang

2022

Mathematical Problems in Engineering

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An improved ORB feature point purification method has been proposed to address the problem of large feature point matching error and low image registration rate in the oriented FAST and rotated BRIEF (ORB) feature point color image matching algorithm. Pure virtual quaternions were used to represent the color image pixels in this method, and an improved FAST algorithm was used to detect the color feature points at first. The firework algorithm has been used to divide the detected feature points into key areas, auxiliary areas, and small influence areas, depending on the degree of attachment. The feature points of the key area and the subsidiary area are the required feature points. In order to further improve the efficiency of matching the color image feature points, the firework explosion radius formula and the explosion number formula in the firework algorithm have been improved, and an improved firework algorithm is proposed. This improved algorithm purifies the quaternion-represented color image feature points. For feature matching, the hamming distance was used. Experiments show that, when compared to the traditional ORB algorithm, the improved algorithm retains the key feature points of the color image with high accuracy, removes a large number of irrelevant feature points and noise points, and provides significantly higher accuracy and efficiency of color image matching.

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Section: Introductionmentioning

confidence: 99%

Color Image Feature Matching Method Based on the Improved Firework Algorithm

Liu

Zhu

Wang

2022

Mathematical Problems in Engineering

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A Comprehensive Review of the Fireworks Algorithm

Tan

2019

ACM Comput. Surv.

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The fireworks algorithm, which is inspired from the phenomenon of fireworks explosion, is a special kind of swarm intelligence algorithm proposed in 2010. Since then, it has been attracting more and more research interest and has been widely employed in many real-world problems due to its unique search manner and high efficiency. In this article, we present a comprehensive review of its advances and applications. We begin with an introduction to the original fireworks algorithm. Then we review its algorithmic research work for single objective and multi-objective optimization problems. After that, we present the theoretical analyses of the fireworks algorithm. Finally, we give a brief overview of its applications and implementations. Hopefully, this article could provide a useful road map for researchers and practitioners who are interested in this algorithm and inspire new ideas for its further development.

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Recent Developments of Fireworks Algorithms

Tan

2020

Handbook of Research on Fireworks Algorithms and Swarm Intelligence

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Fireworks Algorithm has been proposed for almost 10 years. Because of its basic but profound collaborative searching manner and advantages of universal effectiveness, hundreds of scholars have conducted and published a wide range of work on it. This chapter serves as a background description of fireworks algorithms' developments by introducing its detailed status of researches and applications. Specifically, it gives a brief summarization and analysis of published researches on Fireworks Algorithms since 2010 to clarify characteristics of its historical progress and future trend in detailed fields like algorithms improvements, theoretical analysis, and practical applications.

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Image retrieval based on fireworks algorithm optimizing convolutional neural network

Cited by 3 publications

References 6 publications

Color Image Feature Matching Method Based on the Improved Firework Algorithm

Color Image Feature Matching Method Based on the Improved Firework Algorithm

A Comprehensive Review of the Fireworks Algorithm

Recent Developments of Fireworks Algorithms

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