Teaching Assistant
Paper ID: 52


  • CNN
  • Optimization
  • Backpropagation
  • Object Recognition

Abstract: This paper exhibits an Object recognition technique using the Convolutional Neural Network in Deep Learning. Backpropagation is a redundantly used method to calculate the gradient of a curve. The gradient, in turn, is involved in the weight upgradation while training the deep neural network. Being a repeatedly rediscovered algorithm, Backpropagation still stands out to give better results with its various optimization techniques. An Object Recognition technique in deep learning using backpropagation, optimized with a heuristic optimization technique is implemented and evaluated.

Paper Link: https://ieeexplore.ieee.org/document/8878719

(Use Sci Hub in case you are not able to access the paper)

Published in: 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)


  1. Implement the model in Tensorflow. Specify the number of layers of each type for the CNN that you are implementing.
  2. Only RMSPROP and Adadelta optimizer results need to be shown.

Data Set: http://www.cs.columbia.edu/CAVE/software/softlib/coil-100.php

Paper ID: 52