Many railway accidents happen under shunting mode. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver to avoid danger....
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ISBN:
(纸本)9781510623354
Many railway accidents happen under shunting mode. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver to avoid danger. However, human error and fatigue will reduce the safety of shunting operation. To address this issue, a novel objectdetection framework for a train automatic detecting objects ahead in shunting mode, called Feature Fusion detection neural network (FFDet). It consists of two connected modules, i.e., the refine detectionmodule and the object detection module. The refine detectionmodule coarsely the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results show that FFDet demonstrates good performance in detecting objects and can meet the needs of practical application in shunting mode.
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