Image Recognition Using Artificial Intelligence

Kumar, Manish; Sharma, Siddharth; Chaudhary, Divy; Prakash, S. Arun

doi:10.1109/icacite51222.2021.9404606

Cited by 6 publications

References 4 publications

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Using machine learning to predict artistic styles: an analysis of trends and the research agenda

Valencia,

Pineda,

Pineda

et al. 2024

Artif Intell Rev

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In the field of art, machine learning models have been used to predict artistic styles in paintings. The foregoing is somewhat advantageous for analysts, as these tools can provide more valuable results and help reduce bias in the results and conclusions provided. Therefore, the objective of this research was to examine research trends in the use of machine learning to predict artistic styles from a bibliometric review based on the PRISMA methodology. From the search equations, 268 documents were found, out of which, following the application of inclusion and exclusion criteria, 128 documents were analyzed. Through quantitative analysis, a growing research interest in the subject is evident, progressing from user perception approaches to the utilization of tools like deep learning for art studies. Among the main results, it is possible to identify that one of the most used techniques in the field has been neural networks for pattern recognition. Also, a large part of the research focuses on the use of design software for image creation and manipulation. Finally, it is found that the number of studies focused on contemporary modern art is still limited, this is due to the fact that a large part of the investigations has focused on historical artistic styles.

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Using machine learning to predict artistic styles: an analysis of trends and the research agenda

Valencia,

Pineda,

Pineda

et al. 2024

Artif Intell Rev

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Early fault diagnosis based on reinforcement learning optimized-SVM model with vibration-monitored signals

Zhao

Liu

et al. 2023

Quality Engineering

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Application of Artificial Intelligence Voice Technology in Radio and Television Media

Hu¹,

Xiang²,

Li³

2021

J. Phys.: Conf. Ser.

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With the application of artificial intelligence in various fields, more and more people see the contribution of artificial intelligence technology to the development of the industry, and put more energy in the research of artificial intelligence language, and strive to provide better technical support for the development of more industries. In radio and television media, artificial intelligence voice technology can play a very important value, it can effectively improve the efficiency and quality of traditional audio work, optimize the singing system, broadcasting system and retrieval system, so as to provide better service quality for the masses. This paper discusses the application and development of artificial intelligence technology based on the fusion media environment, analyzes the application and development of artificial intelligence technology in promoting production efficiency, intelligent robot writing, intelligent face recognition, intelligent speech semantic recognition, intelligent OCR recognition, automatic broadcast and other aspects. These AI applications provide efficient and secure support for services, greatly improving service efficiency.

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Image Recognition Using Artificial Intelligence

Cited by 6 publications

References 4 publications

Using machine learning to predict artistic styles: an analysis of trends and the research agenda

Using machine learning to predict artistic styles: an analysis of trends and the research agenda

Early fault diagnosis based on reinforcement learning optimized-SVM model with vibration-monitored signals

Application of Artificial Intelligence Voice Technology in Radio and Television Media

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