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A Study on Convolutional Neural Networks with Active Video Tubelets for Object Detection and Classification

  • R. Rajkumar
  • J. ArunnehruEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)

Abstract

Convolutional neural networks are a powerful learning model inspired from biological concept of neurons. This deep learning model allows us to replicate the complex neural structure seen in living beings to be applied on data sets and to structure convulsions consisting of several layers. A study on convolutional neural networks have been proven to be an effective class of models for object recognition, taking those results into consideration we intend to apply convolutional neural networks for video classification in two different ways. Generalization of the results obtained by the application of convolutional neural networks on existing data sets for videos, namely Sports 1-M and YouTube object data set (YTO) and their implementation of two distinct CNNs.

Keywords

Convolutional neural networks Deep learning Object detection Video Tubelets Video classification 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSRM Institute of Science and TechnologyChennaiIndia

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