Object Recognition Using Deep Neural Networks: A Survey

12/10/2014
by   Soren Goyal, et al.
0

Recognition of objects using Deep Neural Networks is an active area of research and many breakthroughs have been made in the last few years. The paper attempts to indicate how far this field has progressed. The paper briefly describes the history of research in Neural Networks and describe several of the recent advances in this field. The performances of recently developed Neural Network Algorithm over benchmark datasets have been tabulated. Finally, some the applications of this field have been provided.

READ FULL TEXT
research
01/19/2017

Deep Neural Networks - A Brief History

Introduction to deep neural networks and their history....
research
08/30/2021

Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions

Visual recognition is currently one of the most important and active res...
research
07/09/2017

Evaluating race and sex diversity in the world's largest companies using deep neural networks

Diversity is one of the fundamental properties for the survival of speci...
research
10/02/2018

NU-LiteNet: Mobile Landmark Recognition using Convolutional Neural Networks

The growth of high-performance mobile devices has resulted in more resea...
research
11/20/2018

Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack

The main goal of the paper is to provide Pepper with a near real-time ob...
research
10/02/2019

Supply-Power-Constrained Cable Capacity Maximization Using Deep Neural Networks

We experimentally achieve a 19 power in a 12-span link by eliminating ga...
research
04/17/2019

Collaboration Analysis Using Deep Learning

The analysis of the collaborative learning process is one of the growing...

Please sign up or login with your details

Forgot password? Click here to reset