output
20192025
most citedAn application of a deep learning algorithm for automatic detection of unexpected accidents under bad CCTV monitoring conditions in tunnels

89 citations

5 papers

eess.SP2025★ 1 cited

Shape-Aware Topological Representation for Pipeline Hyperbola Detection in GPR Data

Meiyan Kang, Shizuo Kaji, Sang-Yun Lee +3

Ground Penetrating Radar (GPR) is a widely used Non-Destructive Testing (NDT) technique for subsurface exploration, particularly in infrastructure inspection and maintenance. Howev…

physics.ao-ph2022★ 8 cited

Global warming in the pipeline

James E. Hansen, Makiko Sato, Leon Simons +14

Improved knowledge of glacial-to-interglacial global temperature change implies that fast-feedback equilibrium climate sensitivity (ECS) is 1.2 +/- 0.3°C (2) per W/m. Consis…

stat.ML2021

An overcome of far-distance limitation on tunnel CCTV-based accident detection in AI deep-learning frameworks

Kyu-Beom Lee, Hyu-Soung Shin

Tunnel CCTVs are installed to low height and long-distance interval. However, because of the limitation of installation height, severe perspective effect in distance occurs, and it…

cs.CV2019★ 89 cited

An application of a deep learning algorithm for automatic detection of unexpected accidents under bad CCTV monitoring conditions in tunnels

Kyu-Beom Lee, Hyu-Soung Shin

In this paper, Object Detection and Tracking System (ODTS) in combination with a well-known deep learning network, Faster Regional Convolution Neural Network (Faster R-CNN), for Ob…

cs.CV2019★ 1 cited

Self-enhancement of automatic tunnel accident detection (TAD) on CCTV by AI deep-learning

Kyu-Beom Lee, Hyu-Soung Shin

The deep-learning-based tunnel accident detection (TAD) system (Lee 2019) has installed a system capable of monitoring 9 CCTVs at XX site in November, 2018. The initial deep-learni…