Deep Learning for Remote Sensing Applications |
Lee, Moung-Jin
(Center for Environmental Data Strategy, Korea Environment Institute)
Lee, Won-Jin (Environmental Satellite Center, National Institute of Environmental Research) Lee, Seung-Kuk (Division of Earth and Environmental System Sciences, Pukyong National University) Jung, Hyung-Sup (Department of Geoinformatics, University of Seoul) |
1 | Yoon, Y.-W., H.-S. Jung, and W.-J. Lee, 2022. YOLOv5-based Chimney Detection Using High Resolution Remote Sensing Images, Korean Journal of Remote Sensing, 38(6-2): 1677-1689 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.9 DOI |
2 | Park, S.-H., D.-S. Kim, and J.-I. Kwon, 2022c. A Study on the GK2A/AMI Image Based Cold Water Detection Using Convolutional Neural Network, Korean Journal of Remote Sensing, 38(6-2): 1653-1661 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.7 DOI |
3 | Lee, S.-H. and M. Lee, 2020. A Study on Deep Learning Optimization by Land Cover Classification Item Using Satellite Imagery, Korean Journal of Remote Sensing, 36(6-2): 1591-1604 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.6.2.9 DOI |
4 | Lee, Y., S. Lee, J. Im, and C. Yoo, 2021. Analysis of Surface Urban Heat Island and Land Surface Temperature Using Deep Learning Based Local Climate Zone Classification: A Case Study of Suwon and Daegu, Korea, Korean Journal of Remote Sensing, 37(5-3): 1447-1460 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.5.3.9 DOI |
5 | Park, C.-W. and H.-S. Jung, 2022. Detection of Urban Trees using YOLOv5 from Aerial Images, Korean Journal of Remote Sensing, 38(6-2): 1633-1641 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.5 DOI |
6 | Park, G., J. Kang, S. Choi, Y. Youn, G. Kim, and Y. Lee, 2022a. Detection of Active Fire Objects from Drone Images Using YOLOv7x Model, Korean Journal of Remote Sensing, 38(6-2): 1737-1741 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.13 DOI |
7 | Park, G., Y. Youn, J. Kang, G. Kim, S. Choi, S. Jang, S. Bak, S. Gong, J. Kwak, and Y. Lee, 2022b. A Comparative Study on the Object Detection of Deposited Marine Debris (DMD) Using YOLOv5 and YOLOv7 Models, Korean Journal of Remote Sensing, 38(6-2): 1643-1652 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.6 DOI |
8 | Seong, S. K., H.-S. Choi, J. S. Mo, and J. Choi, 2021a. Availability Evaluation of Object Detection Based on Deep Learning Method by Using Multitemporal and Multisensor Data for Nuclear Activity Analysis, Korean Journal of Remote Sensing, 37(5-1): 1083-1094 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.5.1.20 DOI |
9 | Cha, S. E., H.-W. Jo, C.-H. Lim, C. Song, S.-G. Lee, J. Kim, C. Park, S. W. Jeon, and W.-K. Lee, 2020. Estimating the Stand Level Vegetation Structure Map Using Drone Optical Imageries and LiDAR Data based on an Artificial Neural Networks (ANNs), Korean Journal of Remote Sensing, 36(5-1): 653-666 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.5.1.1 DOI |
10 | Baek, W.-K. and H.-S. Jung, 2022. A Review on Deep-learning-based Phase Unwrapping Technique for Synthetic Aperture Radar Interferometry, Korean Journal of Remote Sensing, 38(6-2): 1589-1605 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.2 DOI |
11 | Cho, Y.-I., D. Yoon, and M.-J. Lee, 2022. Analysis of Spatial Correlation between Surface Temperature and Absorbed Solar Radiation Using Drone - Focusing on Cool Roof Performance, Korean Journal of Remote Sensing, 38(6-2): 1607-1622 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.3 DOI |
12 | Choi, Y., M. Kim, Y. Kim, and S. Han, 2020b. A Study of CNN-based Super-Resolution Method for Remote Sensing Image, Korean Journal of Remote Sensing, 36(3): 449-460 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.3.5 DOI |
13 | Jeon, E.-I., S.H. Kim, B.-S. Kim, K.H. Park, and O. Choi, 2020. Semantic Segmentation of Drone Imagery Using Deep Learning for Seagrass Habitat Monitoring, Korean Journal of Remote Sensing, 36(2-1): 199-215 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.2.1.8 DOI |
14 | Jeong, M., H. Choi, and J. Choi, 2020. Analysis of Change Detection Results by UNet++ Models According to the Characteristics of Loss Function, Korean Journal of Remote Sensing, 36(5-2): 929-937 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.5.2.7 DOI |
15 | Kim, J., H. Jeon, and D.-J. Kim, 2020b. Extracting Flooded Areas in Southeast Asia Using SegNet and U-Net, Korean Journal of Remote Sensing, 36(5-3): 1095-1107 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.5.3.8 DOI |
16 | Seong, S.K., J.S. Mo, S.-I. Na, and J. Choi. 2021b. Attention Gated FC-DenseNet for Extracting Crop Cultivation Area by Multispectral Satellite Imagery, Korean Journal of Remote Sensing, 37(5-1): 1061-1070 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.5.1.18 DOI |
17 | Mo, J.S., S.K. Seong, and J. Choi, 2021. Change Detection of Building Objects in Urban Area by Using Transfer Learning, Korean Journal of Remote Sensing, 37(6-1): 1685-1695 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.6.1.16 DOI |
18 | Kang, J., G. Kim, Y. Jeong, S. Kim, Y. Youn, S. Cho, and Y. Lee, 2021. U-Net Cloud Detection for the SPARCS Cloud Dataset from Landsat 8 Images, Korean Journal of Remote Sensing, 37(5-1): 1149-1161 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.5.1.25 DOI |
19 | Kang, J., G. Park, G. Kim, Y. Youn, S. Choi, and Y. Lee, 2022a. Cloud Detection from Sentinel-2 Images Using DeepLabV3+ and Swin Transformer Models, Korean Journal of Remote Sensing, 38(6-2): 1743-1747 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.14 DOI |
20 | Kim, E., K. Kim, S. M. Kim, T. Cui, and J.-H. Ryu, 2020a. Deep Learning Based Floating Macroalgae Classification Using Gaofen-1 WFV Images, Korean Journal of Remote Sensing, 36(2-2): 293-307 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.2.2.6 DOI |
21 | Kim, N., M.-S. Park, M. J. Jeong, D.-H. Hwang, and H.-J. Yoon, 2021b. A Study on Field Compost Detection by Using Unmanned Aerial Vehicle Image and Semantic Segmentation Technique based Deep Learning, Korean Journal of Remote Sensing, 37(3): 367-378 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.3.1 DOI |
22 | Ko, K.-S., Y.-W. Kim, S.-H. Byeon, and S.-J. Lee, 2021. LSTM Based Prediction of Ocean Mixed Layer Temperature Using Meteorological Data, Korean Journal of Remote Sensing, 37(3): 603-614 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.3.19 DOI |
23 | Kim, J., Y. Song, and W.-K. Lee, 2021a. Accuracy analysis of Multi-series Phenological Landcover Classification Using U-Net-based Deep Learning Model - Focusing on the Seoul, Republic of Korea, Korean Journal of Remote Sensing, 37(3): 409-418 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.3.4 DOI |
24 | Baek, W.-K., M.-J. Lee, and H.-S. Jung, 2022. The Performance Improvement of U-Net Model for Landcover Semantic Segmentation through Data Augmentation, Korean Journal of Remote Sensing, 38(6-2): 1663-1676 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.8 DOI |
25 | Choi, H., D. Seo, and J. Choi, 2020a. A Pansharpening Algorithm of KOMPSAT-3A Satellite Imagery by Using Dilated Residual Convolutional Neural Network, Korean Journal of Remote Sensing, 36(5-2): 961-973 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.5.2.10 DOI |
26 | Gong, S.-H., W.-K. Baek, and H.-S. Jung, 2022. Landslide Susceptibility Mapping Using Deep Neural Network and Convolutional Neural Network, Korean Journal of Remote Sensing, 38(6-2): 1723-1735 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.12 DOI |
27 | Song, C., W. Wahyu, J. Jung, S. Hong, D. Kim, and J. Kang, 2020. Urban Change Detection for High-resolution Satellite Images Using U-Net Based on SPADE, Korean Journal of Remote Sensing, 36(6-2): 1579-1590 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.6.2.8 DOI |
28 | Chung, D. and I. Lee, 2021. The Optimal GSD and Image Size for Deep Learning Semantic Segmentation Training of Drone Images of Winter Vegetables, Korean Journal of Remote Sensing, 37(6-1): 1573-1587 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2021.37.6.1.7 DOI |
29 | Jung, S.H., Y.J. Kim, S. Park, and J. Im, 2020. Prediction of Sea Surface Temperature and Detection of Ocean Heat Wave in the South Sea of Korea Using Time-series Deep-learning Approaches, Korean Journal of Remote Sensing, 36(5-3): 1077-1093 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.5.3.7 DOI |
30 | Kang, J., Y. Youn, G. Kim, G. Park, S. Choi, C.-S. Yang, J. Yi, and Y. Lee, 2022b. Detection of Marine Oil Spills from PlanetScope Images Using DeepLabV3+ Model, Korean Journal of Remote Sensing, 38(6-2): 1623-1631 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.4 DOI |
31 | Yu, J.W., Y.-W. Yoon, E.-R. Lee, W.-K. Baek, and H.-S. Jung, 2022. Flood Mapping Using Modified U-NET from TerraSAR-X Images, Korean Journal of Remote Sensing, 38(6-2): 1709-1722 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.11 DOI |
32 | Lee, E.-R., H.-S. Lee, S.-C. Park, and H.-S. Jung, 2022. Observation of Ice Gradient in Cheonji, Baekdu Mountain Using Modified U-Net from Landsat -5/-7/-8 Images, Korean Journal of Remote Sensing, 38(6-2): 1691-1707 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2022.38.6.2.10 DOI |
33 | Seong, S.K., S.-I. Na, and J. Choi, 2020. Assessment of the FC-DenseNet for Crop Cultivation Area Extraction by Using RapidEye Satellite Imagery, Korean Journal of Remote Sensing, 36(5-1): 823-833 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.5.1.14 DOI |
34 | Lee, J., C. Yoo, J. Im, Y. Shin, and D. Cho, 2020. Multitask Learning Based Tropical Cyclone Intensity Monitoring and Forecasting through Fusion of Geostationary Satellite Data and Numerical Forecasting Model Output, Korean Journal of Remote Sensing, 36(5-3): 1037-1051 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2020.36.5.3.4 DOI |