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Yifan Liu, Qigang Zhu, Feng Cao, Junke Chen and Gang Lu
Semantic segmentation has been widely used in the basic task of extracting information from images. Despite this progress, there are still two challenges: (1) it is difficult for a single-size receptive field to acquire sufficiently strong representation...
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Jianfeng Zhu, Lichun Sui, Yufu Zang, He Zheng, Wei Jiang, Mianqing Zhong and Fei Ma
In various applications of airborne laser scanning (ALS), the classification of the point cloud is a basic and key step. It requires assigning category labels to each point, such as ground, building or vegetation. Convolutional neural networks have achie...
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Bilel Benjdira, Adel Ammar, Anis Koubaa and Kais Ouni
Despite the significant advances noted in semantic segmentation of aerial imagery, a considerable limitation is blocking its adoption in real cases. If we test a segmentation model on a new area that is not included in its initial training set, accuracy ...
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Gang Zhang, Tao Lei, Yi Cui and Ping Jiang
Semantic segmentation on high-resolution aerial images plays a significant role in many remote sensing applications. Although the Deep Convolutional Neural Network (DCNN) has shown great performance in this task, it still faces the following two challeng...
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