Paper Title

AI IMAGE GENERATION WITH DALL-E AND STABLE DIFFUSION: A SURVEY

Article Identifiers

Registration ID: IJNRD_216396

Published ID: IJNRD2403542

DOI: Click Here to Get

Authors

Rahul Sharma , Harsh Jaiswal , Nakul Singh Jadon , Charul Bapna

Keywords

AI, Image generation, Generative, DALL-E, Diffusion, Deep learning, Optimization, Virtual, Unsupervised learning, text-to-image generation

Abstract

Image generation has advanced significantly because of recent advances in artificial intelligence (AI), allowing machines to produce realistic photographs that nearly match those taken by humans. A thorough overview of AI image creation models is given in this survey, with an emphasis on the models' architectures, training methods, and applications. We categorize these models, along with their extensions and modifications, we categorize these models as the Stable Diffusion model and the DALL-E model. We go over the fundamental ideas of each model class and highlight their salient features and competencies. In addition, we offer a comparison of these models according to their scalability and computational complexity. Furthermore, we investigate the uses of image generation in a variety of industries, such as entertainment, fashion, content creation and design for demonstrating the usefulness and promise of these models in real-world contexts. Lastly, we analyze the drawbacks and limitations of the models currently used by AI to generate images and suggest future lines of inquiry to resolve these problems and improve AI's ability to produce realistic images.

How To Cite

"AI IMAGE GENERATION WITH DALL-E AND STABLE DIFFUSION: A SURVEY", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 3, page no.f369-f372, March-2024, Available :https://ijnrd.org/papers/IJNRD2403542.pdf

Issue

Volume 9 Issue 3, March-2024

Pages : f369-f372

Other Publication Details

Paper Reg. ID: IJNRD_216396

Published Paper Id: IJNRD2403542

Downloads: 000121166

Research Area: Computer Science & Technology 

Country: Jaipur, Rajasthan, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403542.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403542

About Publisher

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

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Call For Paper

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.

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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