Model Selection Procedure in Alleviating Drawbacks of the Electronic Whiteboard

Title

Model Selection Procedure in Alleviating Drawbacks of the Electronic Whiteboard

Creator

Jha S.

Description

Deep learning has paved the way for critical and revolutionary applications in almost every field of life in general. Ranging from engineering to healthcare, machine learning and deep learning has left its mark as the state-of-the-art technology application which holds the epitome of a reasonable high benchmarked solution. Incorporating neural network architectures into applications has become a common part of any software development process. In this paper, we perform a comparative analysis on the different transfer learning approaches in the domain of hand-written digit recognition. We use two performance measures, loss and accuracy. We later visualize the different results for the training and validation datasets and reach to a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with simultaneous focus on the suitable model selection procedure for the digit recognition problem. 2021 IEEE.

Source

Proceedings - 2021 3rd International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2021, pp. 319-322.

Date

2021-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Deep Learning; Electronic Whiteboard; Learning; Machine Learning; Transfer Learning

Coverage

Jha S., Christ University, School of Science, New Delhi, India

Rights

Restricted Access

Relation

ISBN: 978-166543811-7

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICAC3N53548.2021.9725365

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126950039&doi=10.1109%2fICAC3N53548.2021.9725365&partnerID=40&md5=188fcf6cef14359fc2cd6d8370de48d8