Teerapong Panboonyuen
Teerapong Panboonyuen
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object-detection
REG: Refined Generalized Focal Loss for Road Asset Detection on Thai Highways Using Vision-Based Detection and Segmentation Models
We are pleased to announce that our paper, titled ‘Enhanced REG-Based Object Detection of Road Assets Utilizing Generalized Focal Loss A Case Study on Thai Highway Imagery’, has been accepted for oral presentation at the 5th International Conference on Highway Engineering (iCHE 2024).
Teerapong Panboonyuen
2024
deep-learning
,
computer-vision
,
object-detection
,
instance-segmentation
Transportation Mobility Factor Extraction Using Image Recognition Techniques
For an urban development, the Quality of Life (QOL) of people in the city is a vital issue that should be considered. There are many researches in QOL topics that use questionnaire survey approach. These studies yield very useful information for city development planning. As the Artificial Intelligence technologies are developed very fast recently, they are applied to solve many transportation problems. In this paper, we propose a method that automatically extract mobility indicators using two image recognition techniques, Semantic Segmentation and Object Recognition. Because the mobility is an important factor in QOL evaluation, our work can be used to enhance a performance and reduce a data gathering cost of the QOL evaluation.
P. Kantavat
,
Y. Hayashi
,
G. City
,
B. Kijsirikul
,
Teerapong Panboonyuen
,
Y. Iwahori
2019
In
First International Conference on Smart Technology & Urban Development
Best Paper; (STUD 2019)
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Best Young Researcher Paper Award
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