A Vision Based DCNN for Identify Bottle Object in Indoor Environment

  • Lolith Gopan
  • R. AarthiEmail author
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 28)


Vision based detection and classification is an emerging area of research in the field of automation. Due to the demand in automation different fields artificial intelligent architectures plays vital role to address the issues. Conventional architectures used for dealing computer vision problems are heavily under control on user features. But the new deep learning techniques have provided a substitute of automatically learning problem related features. The classification problem can be designed based on feature learned from DCNN. The performance of the DCNN algorithm vary based on the training. In this paper the performance of Deep Convolutional Neural Network (DCNN) is analyzed in classifying categories of bottle object.


Deep convolutional neural network (DCNN) Maxpooling Classification 



We would like to extend the heartfelt gratitude to the faculty-in-charge of Amrita-Cognizant Innovation Lab, Department of Computer science and Engineering, Amrita school of Engineering, Coimbatore for the support extended in carrying out this work.


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Copyright information

© Springer International Publishing AG  2018

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Amrita School of Engineering, CoimbatoreAmrita Vishwa Vidyapeetham, Amrita UniversityCoimbatoreIndia

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