Implementing AI for Image Transformation using Next.js

Abstract: The rapid advancement of artificial intelligence (AI) has transformed image Transformation by enabling automated enhancements such as object removal, restoration, recoloring, and generative modifications. The proposed system leverages deep learning models and cloud-based AI services to provide users with an intuitive platform for advanced image modifications while ensuring scalability, security, and efficiency. The architecture features a modular approach, incorporating secure authentication, a credit-based transaction system, and seamless media storage. Benchmark evaluations demonstrate high Transformation accuracy and reduced latency, making AI-driven transformations accessible to non-experts. This study highlights the role of AI in modern web-based image Transformation and presents a scalable solution for real-time, cloudpowered image enhancements

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-03-24
DOI
https://doi.org/10.22214/ijraset.2025.67774
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
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article

Implementing AI for Image Transformation using Next.js

Tanvi Kadam, Ritesh Dhumak, Rudra Bamane, Prithviraj Kharate et al.
International Journal for Research in Applied Science and Engineering Technology
Medical Imaging and Analysis
article

Implementing AI for Image Transformation using Next.js

Tanvi Kadam, Ritesh Dhumak, Rudra Bamane, Prithviraj Kharate, Gaurav Shete
article en

Abstract

Abstract: The rapid advancement of artificial intelligence (AI) has transformed image Transformation by enabling automated enhancements such as object removal, restoration, recoloring, and generative modifications. The proposed system leverages deep learning models and cloud-based AI services to provide users with an intuitive platform for advanced image modifications while ensuring scalability, security, and efficiency. The architecture features a modular approach, incorporating secure authentication, a credit-based transaction system, and seamless media storage. Benchmark evaluations demonstrate high Transformation accuracy and reduced latency, making AI-driven transformations accessible to non-experts. This study highlights the role of AI in modern web-based image Transformation and presents a scalable solution for real-time, cloudpowered image enhancements

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(3)
Universal Engineering College (IN)
Openalex Percentile: Top 95%
Medical Imaging and Analysis
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