Priyadarshani Singh
Biographic Data
| ID | 8969256 |
|---|---|
| NAME | Priyadarshani Singh |
| GIVEN NAMES | Priyadarshani |
| FAMILY NAME | Singh |
| SIGNATURE | SINGH P |
| AFFILIATIONS | Noida International University |
| VERIFIED | No |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 9 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Managing Digital Photography Assets With Ai Tools
The management of high-resolution photographs collections in large quantities has been complicated by the fact that the volumes of images, their heterogeneous file formats and full but usually sporadic metadata has grown exponentially. Manual and rule-based Digital Asset Management (DAM) systems are not conducive to the efficient organization, retrieval and re-use of photographic assets, especially by the professional photographer and creative in…
Generative Ai for Reviving Lost Art Traditions
The disappearance of ancient forms of art can be seen as a great loss of cultural knowledge not only in the form of physical objects but also as symbolic meaning, stylistic grammar, and practice in aesthetic. Although current digital heritage projects focus on documentation, and preservation, they do not offer much assistance in the active revival of art. The ethically-based structure of the AI-driven reconstruction of the lost art traditions is …
Management of Online Art Education Platforms
Ecosystems of online art education have become rich online spaces, combining creative pedagogy and smart technology and data-driven management. The research explores a global governance and operational system that combines artificial intelligence and cloud services with ethical policies to provide more accessibility, quality, and sustainability in the learning of digital art. The study identifies the use of human-AI hybrids in enhancing the learn…
Managing Art Residencies Using Ai Platforms
The adding of Artificial Intelligence (AI) into the administration of art residencies is altering how institutions are producing, staging and promoting creative practice. Below we explain the hybrid field at the crossroad of AI technology and arts administration, and how intelligent systems can be applied to achieve more intelligent decision-making, more efficient resources allocation, and improved artist-institution relations. Despite the recent…
Deep Learning for Photorealistic Rendering in Art Education
It has altered the environment of art education, as deep learning techniques provide a three-dimensional visual experience and creative opportunities of a scale never seen before. It is a study that dwells on the application of convolutional neural networks (CNNs) and generative adversarial networks (GANs) and diffusion models in generating artistic scenes, high fidelity and photorealistic images and simulations to teach. The system that employs …
Deep Learning for Symbol Recognition in Modern Art
Modern art has symbolism, which goes beyond the literal, bringing its meaning in the form of abstraction, geometry, and color. This paper outlines a hybrid deep-learning model that is a combination between the fields of artistic semiotics and computational perception to conduct automated recognition of symbols in contemporary and modern artworks. The given architecture is a combination of Convolutional Neural Networks (CNNs) to analyze local text…
Ai-Based Noise Reduction in Artistic Photography
The AI-driven noise-reduction has become a game-changer in artistic photography, which allows restoring, improving, and preserving the style of a wide variety of visual fields. Conventional methods of denoising like bilateral filtering, wavelet shrinkage, and non-local means tend to be at a loss on how to trade off noise with texture especially in artistic photography where grain, contrast changes, and tonal fading hold aesthetic value. Recent de…
Predictive Models for Creative Talent Identification
Creative talent is a multidimensional human ability that cannot be evaluated fully by traditional assessments based solely on portfolios, standardised tasks or subjective evaluation. In this paper, a multimodal predictive architecture is proposed that fuses textual, visual and behavioural data to predict creative potential more accurately, at a scale and with fairness that is achievable to human standards. In particular, it uses language models b…
Folk Art Tourism Management Using Predictive Systems
Traditional Folk Art Tourism Management has been changed by the incorporation of artificial intelligence and predictive analytics in cultural heritage and tourism. The proposed study will offer a predictive system that can improve the management, promotion, and sustainability of folk art tourism based on data-driven information. The system is predictive of tourists by estimating the number of visitors, seasonal variations, social media usage and …
No prominent works on this page.
Management of Online Art Education Platforms
Ecosystems of online art education have become rich online spaces, combining creative pedagogy and smart technology and data-driven management. The research explores a global governance and operational system that combines artificial intelligence and cloud services with ethical policies to provide more accessibility, quality, and sustainability in the learning of digital art. The study identifies the use of human-AI hybrids in enhancing the learn…
Managing Art Residencies Using Ai Platforms
The adding of Artificial Intelligence (AI) into the administration of art residencies is altering how institutions are producing, staging and promoting creative practice. Below we explain the hybrid field at the crossroad of AI technology and arts administration, and how intelligent systems can be applied to achieve more intelligent decision-making, more efficient resources allocation, and improved artist-institution relations. Despite the recent…
Deep Learning for Photorealistic Rendering in Art Education
It has altered the environment of art education, as deep learning techniques provide a three-dimensional visual experience and creative opportunities of a scale never seen before. It is a study that dwells on the application of convolutional neural networks (CNNs) and generative adversarial networks (GANs) and diffusion models in generating artistic scenes, high fidelity and photorealistic images and simulations to teach. The system that employs …
Deep Learning for Symbol Recognition in Modern Art
Modern art has symbolism, which goes beyond the literal, bringing its meaning in the form of abstraction, geometry, and color. This paper outlines a hybrid deep-learning model that is a combination between the fields of artistic semiotics and computational perception to conduct automated recognition of symbols in contemporary and modern artworks. The given architecture is a combination of Convolutional Neural Networks (CNNs) to analyze local text…
Ai-Based Noise Reduction in Artistic Photography
The AI-driven noise-reduction has become a game-changer in artistic photography, which allows restoring, improving, and preserving the style of a wide variety of visual fields. Conventional methods of denoising like bilateral filtering, wavelet shrinkage, and non-local means tend to be at a loss on how to trade off noise with texture especially in artistic photography where grain, contrast changes, and tonal fading hold aesthetic value. Recent de…
Predictive Models for Creative Talent Identification
Creative talent is a multidimensional human ability that cannot be evaluated fully by traditional assessments based solely on portfolios, standardised tasks or subjective evaluation. In this paper, a multimodal predictive architecture is proposed that fuses textual, visual and behavioural data to predict creative potential more accurately, at a scale and with fairness that is achievable to human standards. In particular, it uses language models b…
Folk Art Tourism Management Using Predictive Systems
Traditional Folk Art Tourism Management has been changed by the incorporation of artificial intelligence and predictive analytics in cultural heritage and tourism. The proposed study will offer a predictive system that can improve the management, promotion, and sustainability of folk art tourism based on data-driven information. The system is predictive of tourists by estimating the number of visitors, seasonal variations, social media usage and …
Managing Digital Photography Assets With Ai Tools
The management of high-resolution photographs collections in large quantities has been complicated by the fact that the volumes of images, their heterogeneous file formats and full but usually sporadic metadata has grown exponentially. Manual and rule-based Digital Asset Management (DAM) systems are not conducive to the efficient organization, retrieval and re-use of photographic assets, especially by the professional photographer and creative in…
Generative Ai for Reviving Lost Art Traditions
The disappearance of ancient forms of art can be seen as a great loss of cultural knowledge not only in the form of physical objects but also as symbolic meaning, stylistic grammar, and practice in aesthetic. Although current digital heritage projects focus on documentation, and preservation, they do not offer much assistance in the active revival of art. The ethically-based structure of the AI-driven reconstruction of the lost art traditions is …
Aesthetic Perception and Analysis (5 works) · Convolutional neural network (3 works) · Digital Media and Visual Art (3 works) · Generative Adversarial Networks and Image Synthesis (3 works) · Perception (3 works) · Creativity (2 works) · Cultural heritage (2 works) · Cultural Industries and Urban Development (2 works) · Deep learning (2 works) · Music Technology and Sound Studies (2 works)