A Comprehensive Study of Applying Convolutional Neural Network for Computer Vision

Abstract

Computer vision makes computers enable to recognize and understand information from
digital images. It is a multidisciplinary field and aims to develop automated systems that able to
extract information from the digital images. Advancements in algorithms and processing
capabilities help to obtain higher accuracy in computer vision tasks. Deep learning offers a set
of computational models that made up with multiple processing layers to learn and represent the
complex data. Convolutional neural network (CNN) is one of deep leaning architecture that
performs various tasks like classification, object detection and segmentation with higher
accuracy and generalization. This paper provides a comprehensive study of different CNN
architectures and its applications for computer vision tasks.