Abstract
Neural networks are often used for classifying images of specific objects, people, animals, and other objects of interest because of their ability to find particular patterns for categories. In this paper, we apply a Convolutional Neural Network (CNN) to classify images from a dataset of 4 semi-ambiguous classes and compare the scores of different architectures of neural networks and how different preprocessing techniques can affect their performance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
