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Home Design Recommendation System Using Machine Learning and AI
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence and Machine Learning
Abstract
In this paper, we introduce InHome Vision, an AI-powered system for inauguration support and interior design recommendations that uses image analysis and machine learning to provide customized home styling options. In order to provide precise and user-centered design recommendations, the suggested model analyzes room photos to find structural elements, color patterns, and design themes. The system incorporates 3D visualization, intelligent recommendations, and service-provider connectivity to improve homeowners' decision-making. The research shows how deep learning and contemporary web technologies can enhance end-to-end interior execution workflows, user interaction, and home design planning.
Keywords
Deep Learning, Interior Design, Recommendation System, Artificial Intelligence, and 3D Visualization.
References
[1] F. Chollet, Deep Learning with Python, Manning Publications, 2018.
[2] J. Zhang and Y. Zheng, “A Review on Deep Learning-Based Interior Scene Classification,” IEEE Access, 2021.
[3] O. Russakovsky et al., “ImageNet Large Scale Visual Recognition Challenge,” International Journal of Computer Vision, 2015.
[4] L. Liu, W. Ouyang, X. Wang, et al., “Deep Learning for Generic Object Detection: A Survey,” International Journal of Computer Vision, 2020.
[5] A. Dosovitskiy et al., “An Image Is Worth 16x16 Words: Transformers for Image Recognition at Scale,” arXiv:2010.11929, 2020.
How to cite this paper
@article{1712202,
author = {Sachin Maurya, Rohit Kumar, Kuldeep, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri},
title = {Home Design Recommendation System Using Machine Learning and AI},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {1650-1651},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712202.pdf},
abstract = {In this paper, we introduce InHome Vision, an AI-powered system for inauguration support and interior design recommendations that uses image analysis and machine learning to provide customized home styling options. In order to provide precise and user-centered design recommendations, the suggested model analyzes room photos to find structural elements, color patterns, and design themes. The system incorporates 3D visualization, intelligent recommendations, and service-provider connectivity to improve homeowners' decision-making. The research shows how deep learning and contemporary web technologies can enhance end-to-end interior execution workflows, user interaction, and home design planning.},
keywords = {Deep Learning, Interior Design, Recommendation System, Artificial Intelligence, and 3D Visualization.},
month = {November},
doi = {https://doi.org/10.64388/IREV9I5-1712202}
}