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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19455
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
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| Paper Title: | Comparative Analysis on Deep Learning Optimization Techniques |
| Authors Name: | P. Alekhya , S. Nitish , Y. Harshitha |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_187446
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| Published Paper Id: | IJRTI2306161 |
| Published In: | Volume 8 Issue 6, June-2023 |
| DOI: | |
| Abstract: | Deep learning & especially Convolutional Neural Networks (CNNs) are taking a different shape in the area of Image Recognition & Classification. Performance of any CNN model depends on various parameters such as size of the dataset, number of classes, weights of the model, hypermeters and mainly on optimizers. Generally, optimizers are used to optimize the model parameters in any learning algorithm. The purpose of an optimizer is to adjust model weights to maximize a loss function. The loss function is used as a way to measure how well the model is performing. In order to reduce the loss and increase the accuracy, we are using the optimizers. In this project, we are doing a comparative analysis of optimizers like mini-batch GD, momentum GD, RMS prop Adam, Adagrad and Adadelta on datasets like MNIST, CIFAR10, Kaggle Flowers. The comparison will be made between the loss and accuracy at every epoch. |
| Keywords: | Deep Learning, Optimizers, SGD, Adam, RMS prop, Adagrad, Adadelta |
| Cite Article: | "Comparative Analysis on Deep Learning Optimization Techniques", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 6, page no.1091 - 1096, June-2023, Available :http://www.ijrti.org/papers/IJRTI2306161.pdf |
| Downloads: | 000205164 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2306161
Registration ID:187446
Published In: Volume 8 Issue 6, June-2023
DOI (Digital Object Identifier):
Page No: 1091 - 1096 Country: Vizanagaram, Andhra Pradesh, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2306161 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2306161 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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