Suksangaram and Yimyam, 2023

technology
Author

Suksangaram and Yimyam

Year of Publication

2023

Conference

International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)

Publisher

IEEE (Bangkok, Thailand)

It is important to note that the specific details of the images and their corresponding crack detection results were not provided in this section. Further sections of the research report may provide more comprehensive information on the results obtained from the system development process.

[…]

Unfortunately, as an AI text-based model, I don’t have access to visual content or the ability to directly display images. I can only assist with generating text-based responses. However, in the context of the research, you can describe the results of the wall crack detection system based on the processed image. For example, you could mention whether the system successfully detected and highlighted the cracks in the image, the accuracy of the detection, and any additional information or analysis provided by the system. To describe the results in detail, you can discuss the visual representation of the image after processing, highlighting the detected cracks or any other relevant information generated by the system.1

This paper was flagged by Lonni Besançon on PubPeer.

Note

The quoted excerpts are from Section III. Experimental Result. There are no results in this section or any following section except for several unexplained figures and an unsubstantiated claim that the system achieved an accuracy of 90%.

References

1Suksangaram W, Yimyam W. The System Operates by Capturing Images of the Wall Surface and Applying Advanced Image Processing Algorithms to Analyze the Visual Data. In: 2023 18th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). IEEE; 2023:1-6. doi:10.1109/iSAI-NLP60301.2023.10354801