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Sejin Lee
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2020 – today
- 2024
- [c7]Mingyu Jeon, Sejin Lee:
Segmentation of Respiratory Bubbles in Underwater Diver Image Using Pixel Coordinate Information and K-Means Clustering. UR 2024: 695-700 - 2022
- [j5]Minji Kim
, Cheonggil Jin
Calibration of BRDF Based on the Field Goniometer System Using a UAV Multispectral Camera. Sensors 22(19): 7476 (2022) - [c6]Eon-Ho Lee, Hyeon Jun Jeon, Jinwoo Choi, Hyun-Taek Choi, Sejin Lee:
Development of Vehicle Detection Method on Water Surface Using LiDAR Data for Situation Awareness. UR 2022: 188-193 - [c5]Chulhee Bae, Yu-Cheol Lee, Wonpil Yu, Sejin Lee:
SPI(Spherical Point Indicator) : Point Feature Image Generation for Point-wise Classification and Dynamic Object Removal. UR 2022: 206-212 - 2021
- [j4]Chulhee Bae
Spherically Stratified Point Projection: Feature Image Generation for Object Classification Using 3D LiDAR Data. Sensors 21(23): 7860 (2021) - 2020
- [j3]Huu-Thu Nguyen
Study on the Classification Performance of Underwater Sonar Image Classification Based on Convolutional Neural Networks for Detecting a Submerged Human Body. Sensors 20(1): 94 (2020) - [j2]Huu-Thu Nguyen
Multiple Object Detection Based on Clustering and Deep Learning Methods. Sensors 20(16): 4424 (2020)
2010 – 2019
- 2019
- [c4]Sejin Lee, Byungjae Park, Ayoung Kim:
A Deep Learning based Submerged Body Classification Using Underwater Imaging Sonar. UR 2019: 106-112 - 2018
- [c3]Chulhee Bae, Sejin Lee:
Object Recognition Using Deep Belief Nets with Spherical Signature Descriptor of 3DPoint Cloud Data for Extended Kalman Filter based Simultaneous Localization and Mapping. UR 2018: 902-907 - [i1]Sejin Lee, Byungjae Park, Ayoung Kim:
Deep Learning from Shallow Dives: Sonar Image Generation and Training for Underwater Object Detection. CoRR abs/1810.07990 (2018) - 2017
- [j1]Donghyun Kim
A New Comprehensive RSU Installation Strategy for Cost-Efficient VANET Deployment. IEEE Trans. Veh. Technol. 66(5): 4200-4211 (2017) - 2016
- [c2]Eon-Ho Lee, Sejin Lee:
Development of underwater terrain's depth map representation method based on occupancy grids with 3D point cloud from polar sonar sensor system. URAI 2016: 497-500 - 2014
- [c1]Junggab Son, Donghyun Kim, Sejin Lee, Heekuck Oh, Alade O. Tokuta, Hayk M. Melikyan:
Trade-off between Service Granularity and User Privacy in Smart Meter Operation. MSN 2014: 288-293
Coauthor Index
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last updated on 2024-08-23 19:22 CEST by the dblp team
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