Detecting and Tracking Sinkholes Using Multi-Level Convolutional Neural Networks and Data Association
Sinkholes can cause severe property damage and threaten public safety. Therefore, the early prediction and detection of sinkholes are important measures for protecting both citizenry and infrastructure. Although many studies have made significant progress on sinkhole detection, challenges remain, in...
Main Authors: | Hoai Nam Vu, Cuong Pham, Nguyen Manh Dung, Soonghwan Ro |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9145527/ |
Similar Items
-
Deepening into the suitability of using pre-trained models of ImageNet against a lightweight convolutional neural network in medical imaging: an experimental study
by: Laith Alzubaidi, et al.
Published: (2021-09-01) -
Sinkholes in Florida and Their Effect on Man's Environment
by: Skinner, Gregory J.
Published: (1972) -
Sinkhole Scanner: A New Method to Detect Sinkhole-Related Spatio-Temporal Patterns in InSAR Deformation Time Series
by: Anurag Kulshrestha, et al.
Published: (2021-07-01) -
Radio–Image Transformer: Bridging Radio Modulation Classification and ImageNet Classification
by: Shichuan Chen, et al.
Published: (2020-10-01) -
Automated Grapevine Cultivar Identification via Leaf Imaging and Deep Convolutional Neural Networks: A Proof-of-Concept Study Employing Primary Iranian Varieties
by: Amin Nasiri, et al.
Published: (2021-08-01)