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A Two-Step Feature Extraction Algorithm: Application to deep learning for point cloud classificationNurunnabi, A. (author), Teferle, F. N. (author), Laefer, D. F. (author), Lindenbergh, R.C. (author), Hunegnaw, A. (author)Most deep learning (DL) methods that are not end-to-end use several multi-scale and multi-type hand-crafted features that make the network challenging, more computationally intensive and vulnerable to overfitting. Furthermore, reliance on empirically-based feature dimensionality reduction may lead to misclassification. In contrast, efficient...journal article 2022
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An efficient deep learning approach for ground point filtering in aerial laser scanning point cloudsNurunnabi, A. (author), Teferle, F. N. (author), Li, J. (author), Lindenbergh, R.C. (author), Hunegnaw, A. (author)Ground surface extraction is one of the classic tasks in airborne laser scanning (ALS) point cloud processing that is used for three-dimensional (3D) city modelling, infrastructure health monitoring, and disaster management. Many methods have been developed over the last three decades. Recently, Deep Learning (DL) has become the most dominant...journal article 2021