발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.5] Accuracy Change According to Image Data and One-Dimensional Array Optimizer |
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| 논문투고자 |
Hyun-Uk Lee, Jin-Suk Bang |
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| 논문내용 |
In the Recently, technologies are becoming more convenient for people's lives due to rapid development. A technology called artificial intelligence is contributing greatly to this development. At the same time, various methods and technologies have been developed to improve the accuracy of artificial intelligence. The accuracy of artificial intelligence is one of the key indicators of how accurately the model performs a given task. To increase this, it is important to properly adjust the type of data and the parameter values of the model, such as epoch, batch-size, and optimizer. However, as technology advances have led to the emergence of numerous parameters and more choices to be made, the process of deciding which values to choose is complicated and time-consuming. Therefore, this study aims to shorten the time to adjust the parameter values required for artificial intelligence development by analyzing and comparing changes in accuracy according to the type of data and the parameter values of the model, epoch, batch-size, and optimizer. Through the study, it is intended to clarify how changes in each parameter affect accuracy and to find the optimal combination. Through this, developers expect to be able to construct artificial intelligence models and improve performance more efficiently. |
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