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Showing 5 of 5 academic articles

DETECTION AND RECOGNITION OF ROAD SIGNS USING YOLOv5

Haitam Ettazi, Najat Rafalia, Jaafar Abouchabaka • Proceedings on Engineering Sciences (2023)

In the field of deep learning, a convolutional neural network is a class of artificial neural networks that became dominant in various computer vision tasks, which is widely used to solve complex problems in various areas, including driver ...

DOAJ Open Access (DOAJ) DOI: 10.24874/PES05.03.017

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

Saleh Albahli, Nudrat Nida, Aun Irtaza, Muhammad Haroon Yousaf et al. • IEEE Access (2020)

Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3035345

DEEP LEARNING-BASED DOOR AND WINDOW DETECTION FROM BUILDING FAÇADE

G. Sezen, M. Cakir, M. E. Atik, Z. Duran • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2022)

Detecting building façade elements is a crucial problem in computer vision for image interpretation. In Building Information Modeling (BIM) studies, the detection of building façade elements has an important role. BIM is a tool that allows ...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLIII-B4-2022-315-2022

Object detection in crowded scenes via joint prediction

Hong-hui Xu, Xin-qing Wang, Dong Wang, Bao-guo Duan et al. • Defence Technology (2023)

Detecting highly-overlapped objects in crowded scenes remains a challenging problem, especially for one-stage detector. In this paper, we extricate YOLOv4 from the dilemma in a crowd by fine-tuning its detection scheme, named YOLO-CS. Speci...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dt.2021.10.007

Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges

Szu-Pyng Kao, Yung-Chen Chang, Feng-Liang Wang • Sensors (2023)

Bridges are often at risk due to the effects of natural disasters, such as earthquakes and typhoons. Bridge inspection assessments normally focus on cracks. However, numerous concrete structures with cracked surfaces are highly elevated or ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23052572