Bhanu Juneja
Biographic Data
| ID | 10127055 |
|---|---|
| NAME | Bhanu Juneja |
| GIVEN NAMES | Bhanu |
| FAMILY NAME | Juneja |
| SIGNATURE | JUNEJA B |
| AFFILIATIONS | Chitkara University |
| ORCID | 0009-0000-4309-6311 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Ai-Based Semantic Tagging of Modern Art Collections
The proposed research will employ deep learning through multimodality and ontology-based reasoning to generate metadata of a modern art collection using an AI-based semantic tagging system. The system uses Vision Transformers (ViT) and BERT/CLIP encoders to pull out visual and textual embeddings and combine them using a contrastive learning method, and align them with cultural ontologies, like the CIDOC-CRM and the Art and Architecture Thesaurus …
Augmented Reality and Ai in Public Art Management
Public art management is becoming increasingly challenged by the swift urbanization, disjointed governance, a lack of interaction with the audience, and a requirement to make data-driven decisions. Artificial Intelligence (AI) and Augmented Reality (AR) have the potential to revolutionize the way people visualize, plan, and monitor and experience public artworks. In this paper, the author suggests an AR-AI framework of managing the public art tha…
Art Curation Algorithms Machine Learning in Museum Education
This paper introduces a consolidated machine learning framework for adaptive art curation for improving museum education. It proposes a system that combines computer vision, natural language processing, recommendation algorithms, and multimodal fusion in order to interpret the works of art and curatorial metadata, and create custom learning pathways given to visitors. A mathematical model is used to formalize the representation of the artwork, th…
Extensive Analysis of Viewer Engagement with Ethnic Minority Representations in Animation
The animated movie creates character performances and movement frame-by-frame by involving a sequence of slightly different objects. The technique involves the development of computer graphics, images, or drawings with creativity. More frequently, the representation of ethnic minorities provides a significant impact on the viewers. So, it is significant to analyze how the viewers are influenced by minority representation in animated movies. Hence…
No prominent works on this page.
Extensive Analysis of Viewer Engagement with Ethnic Minority Representations in Animation
The animated movie creates character performances and movement frame-by-frame by involving a sequence of slightly different objects. The technique involves the development of computer graphics, images, or drawings with creativity. More frequently, the representation of ethnic minorities provides a significant impact on the viewers. So, it is significant to analyze how the viewers are influenced by minority representation in animated movies. Hence…
Ai-Based Semantic Tagging of Modern Art Collections
The proposed research will employ deep learning through multimodality and ontology-based reasoning to generate metadata of a modern art collection using an AI-based semantic tagging system. The system uses Vision Transformers (ViT) and BERT/CLIP encoders to pull out visual and textual embeddings and combine them using a contrastive learning method, and align them with cultural ontologies, like the CIDOC-CRM and the Art and Architecture Thesaurus …
Augmented Reality and Ai in Public Art Management
Public art management is becoming increasingly challenged by the swift urbanization, disjointed governance, a lack of interaction with the audience, and a requirement to make data-driven decisions. Artificial Intelligence (AI) and Augmented Reality (AR) have the potential to revolutionize the way people visualize, plan, and monitor and experience public artworks. In this paper, the author suggests an AR-AI framework of managing the public art tha…
Art Curation Algorithms Machine Learning in Museum Education
This paper introduces a consolidated machine learning framework for adaptive art curation for improving museum education. It proposes a system that combines computer vision, natural language processing, recommendation algorithms, and multimodal fusion in order to interpret the works of art and curatorial metadata, and create custom learning pathways given to visitors. A mathematical model is used to formalize the representation of the artwork, th…
Aesthetic Perception and Analysis (3 works) · Cultural heritage (2 works) · Metadata (2 works) · 3D Surveying and Cultural Heritage (1 work) · Animation (1 work) · Anthropology (1 work) · Architecture (1 work) · Art Education and Development (1 work) · Augmented reality (1 work) · Citizen journalism (1 work)