A Basic Study on Railway Facility Extraction Using a SingleShot MultiBox Detector In railway facilities, there are numerous types and electric trainline facilities. It is difficult to visually inspect all of them, so automatic visual inspection is expected. To achieve automatic inspection, it is important to extract and diagnose the target facilities. This study focuses on facilities extraction by utilizing singleshot multibox detector (SSD), which can be used as a discriminator for human, car and boat object detection, etc. Diagnosis using Local Subspace Classifier (LSC) is proposed. Herein, we present the evaluation results and the issues applying SSD to the equipment called hangers connecting overhead lines. Some diagnosis results are also explained.

ComerLinePrediction based Watertank Detection and Localization Water tanks on the roof of buildings require regular laborcosting inspection, and object detection can be used to automate the task. Current detection frameworks have several drawbacks when they are applied: (1) The output horizontal rectangular boxes cannot provide arbitrary quadrilateral detection representations; (2) False positive results may easily appear when keypoint based models are used. In this paper, we propose a novel detection framework: CornerLinePrediction, which generates tight quadrilateral detection results of the tank blocks. Our model is built on key point detection network to detect corner points precisely. And an original line predictor is integrated to recognize unique tank edges, such that numerous false positive detections can be suppressed. Experimental results show that our CornerLinePrediction (CLP) framework outperforms state oftheart detection algorithms in averageprecision (AP) and produces better localization results, compared with mainstream general detection models.