Dual-discriminator conditional generative adversarial network optimized with hybrid manta ray foraging optimization and volcano eruption algorithm for hyperspectral anomaly detection

Shanmugam, Priyadarshini; Amali, Suthanthira Amalraj Miruna Joe

doi:10.1016/j.eswa.2023.122058

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…On the other hand, the richness of hyperspectral data as a disadvantage brings quite a few significant problems that are coming from difficulty to process effectively and deal with complication. Within the context of anomaly detection in these regions, the requirements of sophisticated analysis tools which can efficiently uncover and decipher the deviations from the expected patterns become a necessity [18][19][20][21][22][23][24][25][26]. framework for interpreting spectral signatures, especially valuable in scenarios with ambiguous conditions [38][39][40][41][42][43][44][45][46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Charting the evolution: bibliometric perspectives on anomaly detection within hyperspectral domains

Obaideen,

Bonny,

AlShabi

2024

Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXX

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In this article the results of the disruption module in the hyperspectral image field are analyzed and present itself. The aim is to see the major concerns, techniques and potential areas that can be researched as topics in the bibliometric method. Highly specified hyper-spectral spectroscopy that can simultaneously analyze the spectral data beyond the visual spectrum down even to the nanoscale. It can be used for various reasons, including environmental management, agriculture, and mineralogy. Unlike small data systems, where patterns are simple to identify, in large scale systems, where there is huge data quantity to study, there should be a wide variety of complexity of algorithms to use in reliable anomaly detection. This research bases its methodology on a two-layer mechanism which is simply to conduct very thorough literature review and deep bibliometric analysis to showcase the innovations in the field of anomaly detection of hyperspectral radar. The role of the states of estimation and the parameters, trained and objective, filtered, control rules, and fuzzy logic are some aspects, among the many, that is coming to the fore during the anomaly detection process. This paper aims to carry out a detailed analysis to mainly focus on the technical and methodological advancements that have reshaped the research area. It also shows that priority should be given to this aspect and that anime detection is the most challenging part of hyperspectral. What is more, this process gives numerous valuable signals about potential routes for future research. The results point to the dominant feature of the developed strategy and analysis which was mostly based on the special of multi-dimensional and transdisciplinary thinking.

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Section: Introductionmentioning

confidence: 99%

Charting the evolution: bibliometric perspectives on anomaly detection within hyperspectral domains

Obaideen,

Bonny,

AlShabi

2024

Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXX

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Phase space deep neural network with Saliency-based attention for hyperspectral target detection

Imani,

Cerra

2024

Advances in Space Research

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A Survey on Manta Ray Foraging Optimization Algorithm of Variants and Applications

Zheng,

Wang,

et al. 2024

International Journal of Swarm Intelligence Research

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This review paper delves into the original MRFO and its variants, focusing on single-objective algorithms including but not limited to hybrid algorithms, learning strategies, multiple populations and dynamic parameter adjustment, highlighting the improvements made to enhance the algorithm's efficiency in global optimization, accelerate convergence rates, and improve its capacity to evade local optima. MRFO has emerged as an effective tool for solving complex optimization problems across various domains, including energy optimization, biomedical field, engineering problems, and others. A comprehensive analysis of applications of MRFO in different fields is provided, emphasizing its adaptability and efficacy. The paper concludes with a discussion on the challenges faced by MRFO and potential future research directions, aiming to consolidate the current research status and guide future investigations.

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Dual-discriminator conditional generative adversarial network optimized with hybrid manta ray foraging optimization and volcano eruption algorithm for hyperspectral anomaly detection

Cited by 3 publications

References 28 publications

Charting the evolution: bibliometric perspectives on anomaly detection within hyperspectral domains

Charting the evolution: bibliometric perspectives on anomaly detection within hyperspectral domains

Phase space deep neural network with Saliency-based attention for hyperspectral target detection

A Survey on Manta Ray Foraging Optimization Algorithm of Variants and Applications

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