Object Detection is an emerging technology in the field of Computer Vision and Image Processing that deals with
detecting objects of a particular class in digital images. It has considered being one of the complicated and challenging tasks in
computer vision. Earlier several machine learning-based approaches like SIFT (Scale-invariant feature transform) and HOG
(Histogram of oriented gradients) are widely used to classify objects in an image. These approaches use the Support vector
machine for classification. The biggest challenges with these approaches are that they are computationally intensive for use in
real-time applications, and these methods do not work well with massive datasets. To overcome these challenges, we implemented
a Deep Learning based approach Convolutional Neural Network (CNN) in this paper. The Proposed approach provides accurate
results in detecting objects in an image by the area of object highlighted in a Bounding Box along with its accuracy.
