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Yunzhuo Liu, Chunjiang Wu, Yuting Zeng, Keyu Chen and Shijie Zhou
Artificial Intelligence has been widely applied in intelligent transportation systems. In this work, Swin-APT, a deep learning-based approach for semantic segmentation and object detection in intelligent transportation systems is presented. Swin-APT incl...
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Joanna Kulawik, Mariusz Kubanek and Sebastian Garus
This research aimed to develop a system for classifying horizontal road signs as correct or with poor visibility. In Poland, road markings are applied by using a specialized white, reflective paint and require periodic repainting. Our developed system is...
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Yongchao Song, Tao Huang, Xin Fu, Yahong Jiang, Jindong Xu, Jindong Zhao, Weiqing Yan and Xuan Wang
Lane line detection is a fundamental and critical task for geographic information perception of driverless and advanced assisted driving. However, the traditional lane line detection method relies on manual adjustment of parameters, and has poor universa...
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Sergey V. Belim and Svetlana Yu. Belim
This article considers the problem of image segmentation based on its representation as an undirected weighted graph. Image segmentation is equivalent to partitioning a graph into communities. The image segment corresponds to each community. The growing ...
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Zhongyu Sun, Wangping Zhou, Chen Ding and Min Xia
Extracting buildings and roads from remote sensing images is very important in the area of land cover monitoring, which is of great help to urban planning. Currently, a deep learning method is used by the majority of building and road extraction algorith...
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John R. Ballesteros, German Sanchez-Torres and John W. Branch-Bedoya
Drone imagery is becoming the main source of overhead information to support decisions in many different fields, especially with deep learning integration. Datasets to train object detection and semantic segmentation models to solve geospatial data analy...
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Cheng Ding, Liguo Weng, Min Xia and Haifeng Lin
Building and road extraction from remote sensing images is of great significance to urban planning. At present, most of building and road extraction models adopt deep learning semantic segmentation method. However, the existing semantic segmentation meth...
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Kai Zhou, Yan Xie, Zhan Gao, Fang Miao and Lei Zhang
Road semantic segmentation is unique and difficult. Road extraction from remote sensing imagery often produce fragmented road segments leading to road network disconnection due to the occlusion of trees, buildings, shadows, cloud, etc. In this paper, we ...
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Azelle Courtial, Achraf El Ayedi, Guillaume Touya and Xiang Zhang
Among cartographic generalisation problems, the generalisation of sinuous bends in mountain roads has always been a popular one due to its difficulty. Recent research showed the potential of deep learning techniques to overcome some remaining research pr...
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Ronald Roberts, Laura Inzerillo and Gaetano Di Mino
Road pavement conditions have significant impacts on safety, travel times, costs, and environmental effects. It is the responsibility of road agencies to ensure these conditions are kept in an acceptable state. To this end, agencies are tasked with imple...
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