Deep Image Learning Using ADAM Classifier

Deep Image Learning Using ADAM Classifier

Registration ID: IJNRD_219863

Published ID: IJNRD2404840

DOI: Click Here to Get

P.Sreenivasulu , S.Vamsi , G. Gopi Krishna , E. Manoj , P. Sai Bhupathi

Deep image classification has seen significant advancements with the advent of deep learning techniques. In this study, we explore the efficacy of the Adam optimization algorithm for training deep neural networks (DNNs) in image classification tasks. Adam, an adaptive learning rate optimization algorithm, has gained popularity for its ability to efficiently optimize large-scale neural networks. We propose a methodology that utilizes Adam to train a deep convolutional neural network (CNN) for image classification tasks. Convolutional Neural Networks (CNNs) have revolutionized the field of computer vision, particularly in image classification tasks. In Data Preparation, Collect a labeled dataset of images suitable for the classification task. Split the dataset into training, validation, and testing sets. In Data Augmentation, Augment the training dataset using techniques such as rotation, flipping, scaling, and cropping to increase variability and improve generalization. In Model Training, Initialize the model parameters (weights and biases) randomly or using pre-trained weights. Train the CNN on the training dataset using back propagation and an optimization algorithm (e.g., Adam, SGD). In Hyperparameter Tuning, Tune hyperparameters such as learning rate, batch size, dropout rate, and regularization strength to optimize model performance. In Model Evaluation, Evaluate the trained model on the test set to assess its performance in terms of accuracy, precision, recall, and F1 score. Visualize performance metrics and analysis any misclassifications or errors. This proposal results demonstrate that Adam offers superior performance in terms of convergence speed and accuracy, making it a promising choice for training deep neural networks in image classification tasks.

Published Paper   E-Certificate

"Deep Image Learning Using ADAM Classifier ", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.i303-i306, April-2024, Available :https://ijnrd.org/papers/IJNRD2404840.pdf

Volume 9 Issue 4, April-2024

Pages : i303-i306

Paper Reg. ID: IJNRD_219863

Published Paper Id: IJNRD2404840

Downloads: 000121125

Research Area: Electronics & Communication Engg. 

Country: Kadapa, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404840.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404840

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

Indexing In Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar | AI-Powered Research Tool, Microsoft Academic, Academia.edu, arXiv.org, Research Gate, CiteSeerX, ResearcherID Thomson Reuters, Mendeley : reference manager, DocStoc, ISSUU, Scribd, and many more

How to submit the paper?

Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area