A Framework for Improving Object Recognition of Structural Components in Construction Site Photos Using Deep Learning Approaches

Park, Sang Mi; Lee, Jae Hee; Kang, Leen Seok

doi:10.1007/s12205-022-2318-0

Cited by 9 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, the Canny operator is used to extract the edges of the segmented image, and the line segment detector algorithm is used to detect the lines in the edge image. The brightness of the image is adjusted based on the boundary-fitting situation [17]. The next step in IP is image stitching, which obtains multiple overlapping images to form a high-resolution image.…”

Section: Design Of Ip Methodsmentioning

confidence: 99%

Detection of Apparent Defects in HPLC/Dual Mode Portable Sorting Device Based on Deep Learning and Image Processing

Wang,

Li,

Jiang

et al. 2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

As the growth of automated detection technology, traditional manual detection has gradually been replaced. To improve the effectiveness of defect detection, a HPLC/dual mode portable sorting device with deep learning and image processing is raised for apparent defect detection. The product image is segmented using flood filled mean shift method, and defect detection is achieved using Yolo v3 algorithm. An LME2918 chip is the main component of the communication module in the portable device. Based on experimental data, image segmentation accuracy can range from 80% to 100%, and image matching accuracy can range from 85% to 95%. Under the power line carrier mode, the average success rate of apparent defect detection in portable sorting devices can reach 85%, and the change in success rate is not significant, indicating that the detection is relatively stable; Under wireless communication mode, the average success rate can reach 83%, and the change in success rate is relatively obvious, because wireless communication is easily affected by the external environment. The experimental data shows that the defect detection effect of the HPLC/dual mode portable sorting device based on deep learning and image processing meets the design requirements.

show abstract

Section: Design Of Ip Methodsmentioning

confidence: 99%