Multi-Output Regression with Generative Adversarial Networks (MOR-GANs)

Phillips, Toby R. F.; Heaney, Claire E.; Benmoufok, Ellyess; Li, Qingyang; Hua, Lily; Porter, Alexandra E.; Chung, Kian Fan; Pain, Christopher C.

doi:10.3390/app12189209

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…Regression analysis is a statistical method used for the analysis and modeling of relationship between variables. This method was selected due to the fact that it enables analyzing the effect of independent variables on the dependent variable and predict the values of the dependent variable on the basis of the values of the independent variables [43].…”

Section: Methodsmentioning

confidence: 99%

Importance of Business Process Quality for Creating Added Value and Raising Reputation of Companies in Low-Carbon Economy

Straková,

Kostiuk

2023

Energies

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In an era of increasing environmental challenges, the transition to a low-carbon economy is an essential step for the manufacturing and industrial sectors. The quality of business processes plays a key role in the transition to a zero-carbon economy. The objective of the paper was, thus, to analyze the break-even point in core and supporting business processes using the proposed linear model based on regression analysis. The aim was to identify the impact of qualitative processes in the pre-production, production, and post-production phases on reaching the break-even point and how these processes affect profits in engineering companies operating in low-carbon sectors. The results suggest that supporting quality processes would generate the highest profit. Investing in improving the quality of core and supporting business processes has a twofold impact, as it improves the bottom line of enterprises through enhancing their reputation as socially responsible businesses. Corporate reputation based on corporate social responsibility in a low-carbon economy represents a valuable intangible asset that helps industrial companies to develop a sustainable and thriving low-carbon business ecosystem.

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Section: Methodsmentioning

confidence: 99%

Importance of Business Process Quality for Creating Added Value and Raising Reputation of Companies in Low-Carbon Economy

Straková,

Kostiuk

2023

Energies

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“…Supervised discriminant analysis relies on labeled data to train the model to distinguish between different classes. In contrast, unsupervised discriminant analysis does not rely on labeled data, but instead classifies and identifies by discovering the intrinsic structure of the data [38]. For unknown samples, whether it is to determine their composition or concentration or to determine their category, it is necessary to apply the established multivariate correction or recognition model combined with the spectral data of the unknown samples for prediction and recognition.…”

Section: Spectral Data Acquisition and Processingmentioning

confidence: 99%

Research on Nondestructive Inspection of Fruits Based on Spectroscopy Techniques: Experimental Scenarios, ROI, Number of Samples, and Number of Features

Wang,

Lu,

Wang

et al. 2024

Agriculture

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Spectral technology is a scientific method used to study and analyze substances. In recent years, the role of spectral technology in the non-destructive testing (NDT) of fruits has become increasingly important, and it is expected that its application in the NDT of fruits will be promoted in the coming years. However, there are still challenges in terms of dataset collection methods. This article aims to enhance the effectiveness of spectral technology in NDT of citrus and other fruits and to apply this technology in orchard environments. Firstly, the principles of spectral imaging systems and chemometric methods in spectral analysis are summarized. In addition, while collecting fruit samples, selecting an experimental environment is crucial for the study of maturity classification and pest detection. Subsequently, this article elaborates on the methods for selecting regions of interest (ROIs) for fruits in this field, considering both quantitative and qualitative perspectives. Finally, the impact of sample size and feature size selection on the experimental process is discussed, and the advantages and limitations of the current research are analyzed. Therefore, future research should focus on addressing the challenges of spectroscopy techniques in the non-destructive inspection of citrus and other fruits to improve the accuracy and stability of the inspection process. At the same time, achieving the collection of spectral data of citrus samples in orchard environments, efficiently selecting regions of interest, scientifically selecting sample and feature quantities, and optimizing the entire dataset collection process are critical future research directions. Such efforts will help to improve the application efficiency of spectral technology in the fruit industry and provide broad opportunities for further research.

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“…Paper [10] explores the use of generative adversarial networks (GANs) for regression tasks, focusing on multi-output regression in non-image data. The study introduces the concept of MOR-GANs, which employ Wasserstein GAN (WGAN) as a regression method.…”

Section: Summary Of the Contributionsmentioning

confidence: 99%