• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• Korean journal of applied entomology
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• v.37 no.2
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• pp.127-135
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• 1998

To study overwintering biology of the oriental tobacco budworm (OTB), Helicoverpaa.ssulta, OTB larvae were collected from middle and southern region of Korea in the autumn and rearedto diapausing pupae. Diapausing pupae were held at two different locations (Suwon and Chinju) and wererecollected in the spring to observe adult emergence rate and duration to adult emergence at 25$^{\circ}$C. Thesurvivorship of overwintering pupae was less than 5% when the pupae were buried in the soil in 20cmdepth. However, more than 60% of the pupae survived when they were kept in the plastic cup withartificial diet and were buried in the soil. The mean developmental periods of overwintering pupae at 25"C varied from 20.4 days to 43.9 days depending on years and locations where larvae were collected andpupae were held. The proportion of individuals which required longer than 30 days for development washigher in the population from the middle regions than those of southern regions. However, the proportiondecreased when the pupae collected from middle regions were held at Chinju, southern region. Chinju, southern region.