Guntaj J
Biographic Data
| ID | 10254141 |
|---|---|
| NAME | Guntaj J |
| GIVEN NAMES | J |
| FAMILY NAME | Guntaj |
| SIGNATURE | J G |
| AFFILIATIONS | Chitkara University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Intelligent Curation of Digital Portfolios for Artists
Intelligent curation represents a novel paradigm of digital art management where AI exists to supplement human creativity to make artistic portfolios more organized, interpreted, and personal. The current work describes a multimodal system consisting of computer vision, transformer-based language models, and reinforcement training that allows creating adaptive, explainable, and human aligning curation. The system evaluates works of art in terms o…
Predictive Ai for Art Investment and Valuation
The conventional approach to art valuation has been based on the subjective judgment of experts and piecemeal market information, which have tended to create inconsistent valuation and a lack of transparency. This paper offers a Predictive AI Framework that combines visual, textual, behavioral and financial data to predict the valuations of works of art with high precision and readability. The model uses ensemble learning based on Gradient Boosti…
No prominent works on this page.
Intelligent Curation of Digital Portfolios for Artists
Intelligent curation represents a novel paradigm of digital art management where AI exists to supplement human creativity to make artistic portfolios more organized, interpreted, and personal. The current work describes a multimodal system consisting of computer vision, transformer-based language models, and reinforcement training that allows creating adaptive, explainable, and human aligning curation. The system evaluates works of art in terms o…
Predictive Ai for Art Investment and Valuation
The conventional approach to art valuation has been based on the subjective judgment of experts and piecemeal market information, which have tended to create inconsistent valuation and a lack of transparency. This paper offers a Predictive AI Framework that combines visual, textual, behavioral and financial data to predict the valuations of works of art with high precision and readability. The model uses ensemble learning based on Gradient Boosti…
Aesthetic Perception and Analysis (2 works) · Analytics (2 works) · Art History and Market Analysis (1 work) · Art, Technology, and Culture (1 work) · Artificial neural network (1 work) · Bespoke (1 work) · Creativity (1 work) · Cultural Industries and Urban Development (1 work) · Deep learning (1 work) · Digital art (1 work)