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In this paper, a novel railway tracks detection and turnouts recognition method using HOG (Histogram of Oriented Gradients) features was presented. At first, the approach computes HOG features and establishes integral images, and then extracts railway tracks by region-growing algorithm.
Feb 8, 2012
A novel railway tracks detection and turnouts recognition method using HOG (Histogram of Oriented Gradients) features was presented, which was able to ...
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A deep learning method for obstacle detection of rail transit was proposed. A color mask method was proposed to divide the region of interest.
We present an ef- ficient row-based rail detection method, Rail-Net, containing a lightweight convolutional backbone and an anchor classifier.
Nov 1, 2021 · The method is based on HOG for extracting features and a support vector machine (SVM) for object detection. These methods achieve reasonable ...
A CNN-based rail track detection algorithm and two novel evaluation metrics are proposed and two track detection metrics are introduced that allow precise ...
This paper presents a way to efficiently use lane detection techniques - known from driver assistance systems - to assist in obstacle detection for ...
论文. 题目, Efficient Railway Tracks Detection and Turnouts Recognition Method using HOG Features. 作者, Qi Z.Q., Tian Y.J., Shi Y. 期刊号, Qi Z.Q., ...
Mar 19, 2024 · This paper introduces the task of “train ego-path detection”, a refined approach to railway track detection designed for intelligent onboard vision systems.
This report has described a new approach for inspecting railway tracks using recent advances in the area of computer vision and pattern recognition. The ...