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이대건(Lee, Dae Geon),이동천(Lee, Dong-Cheon) 한국측량학회 2020 한국측량학회 학술대회자료집 Vol.2020 No.7
Object recognition and classification are important in high-level image processing such as computer vision and machine learning. Detection, recognition, identification, and classification are sequential and progressive learning procedures. However, implementation of human-like learning mechanism using artificial neural network (ANN) with limited training data is challenging task. This paper proposes deep learning for land cover classification using shaded relief maps created from DSM as training data sets. The results show that the derived feature information from original data increases number of training data and improves performance of ANN.