Object detection using deep neural networks

Abstract

The problem discussed in this article is object detection using deep neural network especially convolution neural networks. Object detection was previously done using only conventional deep convolution neural network whereas using regional based convolution network [3] increases the accuracy and also decreases the time required to complete the program. The dataset used is PASCAL VOC 2012 which contains 20 labels. The dataset is very popular in image recognition, object detection and other image processing problems. Supervised learning is also possible in implementing the problem using Decision trees or more likely SVM. But neural network work best in image processing because they can handle images well.