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haar-training

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System detects vehicle density at traffic junctions and allots the required time to traffic lights for vehicle passage dynamically. Classifier is trained using positive and negative images. Further, Adaptive Boosting is used to combine a number of weak classifiers into a strong one. The outcome of AdaBoost is Trained Cascade, which is finally us…

  • Updated Jan 14, 2018
  • Java

The interface of the autonomous car with the surroundings must be similar to that of human way of interaction. Humans use their eyes as a source of vision and then processes the visual signals in his/her brain and takes the necessary action accordingly. Similarly the autonomous car uses a camera as a visual source to know its surrounding, path e…

  • Updated Sep 8, 2018
  • C++

The repository is a part of an experiment, where a Stereo camera sensor was developed for Object detection and distance calculation using machine learning with HAAR-CASCADE- Classifier for an Autonomous Car. The idea was to compare the accuracy of a Stereo camera with that of LiDar sensors to cut down the overall cost of the system.

  • Updated Jun 30, 2019

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