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Dergiler / Türkiye Uzaktan Algılama Dergisi / 2026 / Volume: 8

A deep neural network based on U-Net for classifying airborne LiDAR data

Fırat Uray(NECMETTIN ERBAKAN UNIVERSITY)0000-0001-9555-3190
Abdullah Varlık(NECMETTİN ERBAKAN ÜNİVERSİTESİ, MÜHENDİSLİK VE MİMARLIK FAKÜLTESİ)0000-0003-2072-3313
Sayfa
—
Yayın Tarihi
2026-03-25
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The results showed that our network model performed well when compared to the LAStools software, with an average F1 score of 86% for our best model across all three classes.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:LiDAR point cloud classification has always been a difficult task.
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Temel Bulgular & Veri:This workflow is built around converting a three-dimensional (3D) LiDAR point cloud to a single two-dimensional (2D) multi-channel image.
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Sonuç & Katkı:The results showed that our network model performed well when compared to the LAStools software, with an average F1 score of 86% for our best model across all three classes.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Deep learning · Fully convolutional network · Remote sensing

Abstract

LiDAR point cloud classification has always been a difficult task. Deep learning (DL) models have recently been widely used in computer vision studies, thanks to rapid advances in machine learning technology. In recent years, deep neural networks (DNN) have been used for classification and segmentation of LiDAR point clouds. We proposed a Fully Convolutional Network (FCN) architecture that can classify LiDAR data. This workflow is built around converting a three-dimensional (3D) LiDAR point cloud to a single two-dimensional (2D) multi-channel image. We tested the performance of our neural network model on the DALES airborne LiDAR dataset. The results showed that our network model performed well when compared to the LAStools software, with an average F1 score of 86% for our best model across all three classes.

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Bu Makaleye Atıf Yap

Uray, F., Varlık, A. (2026). A deep neural network based on U-Net for classifying airborne LiDAR data. Türkiye Uzaktan Algılama Dergisi, Volume: 8. https://doi.org/10.51489/tuzal.1778332

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