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Creators/Authors contains: "Kurup, A. R."

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  1. ; (, Lecture notes in computer science)
    Pedestrian Detection in real world crowded areas is still one of the challenging categories in object detection problems. Various mod- ern detection architectures such as Faster R-CNN, R-FCN and SSD has been analyzed based on speed and accuracy measurements. These mod- els can detect multiple objects with overlaps and localize them using a bounding box framing it. Evaluation of performance parameters pro- vides high speed models which can work on live stream applications in mobile devices or high accurate models which provide state-of-the-art performance for various detection problems.These convolutional neural network models are tested on the Penn-Fudan Dataset as well as Google images with occlusions, which achieves high detection accuracies on each of the detectors. 
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