Comparative Study of Various Convolutional Neural Networks on Cifar-10 | Zendy

Tushar Goyal | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Comparative Study of Various Convolutional Neural Networks on Cifar-10

Author(s) -

Tushar Goyal

Publication year - 2020

Publication title -

international journal for modern trends in science and technology

Language(s) - English

Resource type - Journals

ISSN - 2455-3778

DOI - 10.46501/ijmtst061276

Subject(s) - convolutional neural network , computer science , artificial intelligence , field (mathematics) , scratch , pattern recognition (psychology) , neocognitron , artificial neural network , state (computer science) , deep learning , image (mathematics) , cellular neural network , machine learning , time delay neural network , mathematics , algorithm , pure mathematics , operating system

Image recognition plays a foundational role in the field of computer vision and there has been extensiveresearch to develop state-of-the-art techniques especially using Convolutional Neural Network (CNN). Thispaper aims to study some CNNs, heavily inspired by highly popular state-of-the-art CNNs, designed fromscratch specifically for the Cifar-10 dataset and present a fair comparison between them.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research