1 citations · 2 across the 5 of their papers we have counts for
5 papers
Few-shot Anomalies Feedback : Damage Vision Mining Opportunity and Embedding Feature Imbalance
Takato Yasuno
Over the past decade, previous balanced datasets have been used to advance deep learning algorithms for industrial applications. In urban infrastructures and living environments, d…
Disaster Anomaly Detector via Deeper FCDDs for Explainable Initial Responses
Takato Yasuno, Masahiro Okano, Junichiro Fujii
Extreme natural disasters can have devastating effects on both urban and rural areas. In any disaster event, an initial response is the key to rescue within 72 hours and prompt rec…
Wooden Sleeper Deterioration Detection for Rural Railway Prognostics Using Unsupervised Deeper FCDDs
Takato Yasuno, Masahiro Okano, Junichiro Fujii
Maintaining high standards for user safety during daily railway operations is crucial for railway managers. To aid in this endeavor, top- or side-view cameras and GPS positioning s…
One-class Damage Detector Using Deeper Fully-Convolutional Data Descriptions for Civil Application
Takato Yasuno, Masahiro Okano, Junichiro Fujii
Infrastructure managers must maintain high standards to ensure user satisfaction during the lifecycle of infrastructures. Surveillance cameras and visual inspections have enabled p…
River Surface Patch-wise Detector Using Mixture Augmentation for Scum-cover-index
Takato Yasuno, Junichiro Fujii, Masazumi Amakata
Urban rivers provide a water environment that influences residential living. River surface monitoring has become crucial for making decisions about where to prioritize cleaning and…