Mahesh Kurulekar
Biographic Data
| ID | 8968317 |
|---|---|
| NAME | Mahesh Kurulekar |
| GIVEN NAMES | Mahesh |
| FAMILY NAME | Kurulekar |
| SIGNATURE | KURULEKAR M |
| AFFILIATIONS | International Institute of Information Technology |
| VERIFIED | No |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Digital Heritage Reconstruction Techniques for Reviving Lost or Damaged Visual Art Traditions
The further reduction of the environment, natural disasters, and human strife have complicated the preservation of the cultural heritage, particularly visual art traditions, even more. Even though effective, there are times when the traditional methods of restoration are not sufficient even in the restoration of highly damaged or lost works. The reconstruction methods of digital heritage have in their turn responded in the form of new solutions t…
Virtual Curation Methods for Organizing Large-Scale International Digital Art Exhibitions
International exhibition of digital art and the rise in worldwide connectivity of cultures have required new strategies of managing large-scale exhibitions. Conventional curation approaches are severely constrained by handling thousands of arts pieces representing different cultural backgrounds, necessitating manual sorting, thematic sorting by hand, and being not very scalable. This study suggests an all-encompassing virtual curation solution th…
Automated Editing Tools for Media Students: A Comparative Study
Purpose: To assess automated editing tools applied in the media education on the basis of technical and pedagogical terms.Methodology: Four categories of automated editing tools were evaluated based on a multi-dimensional model based on the level of automation, usability, creative control, pedagogical compatibility, and workflow efficiency. A student case study based on tasks was added to quantitative scoring.Results: The results show that high a…
Predictive Analytics for Folk Art Material Requirements
Predictive analytics is a more rational direction of converting material planning to the old folk art manufacturing systems. The use of experiential estimation tends to create shortages in materials, excessive stocking and unviable use of resources further enhanced by seasons and change in demand in the market. To overcome such difficulties, a hybrid forecasting model was created that would have incorporated ARIMA, XGBoost, and LSTM models to for…
Intelligent Systems for Digital Exhibition Design
The study evaluates the evolution and the use of smart systems in designing digital exhibits with the key aspects of how artificial intelligence (AI), machine learning, and immersive technologies can redefine the conventional exhibition models into responsive, interactive, and data-driven cultural experiences. Combining computational intelligence with the human imagination, the study shows that AI-aided curation can boost aesthetic expression, as…
Data Visualization as a Form of Sculptural Art
Data visualization, the interconnection of information and sculptural art is a new paradigm where information moves out of the digital screens and finds space in the physical world to express itself. This paper examines the conceptual, aesthetic and technological systems that allow the data to be physically realized as three dimensional artworks. It investigates how datasets are transformed algorithmically and modeled computationally into forms t…
Music Sentiment Analytics: Understanding Audience Reactions Using Multi-Modal Data From Streaming Platforms
Streaming services are adding more and more user-generated content, which provides us valuable insight on how people feel and how involved they are. Knowing how people feel and react to music may help to make music selection systems, marketing strategies, and outreach efforts to musicians much more efficient. This paper investigates how multi-modal information could be utilised for temper evaluation in song by means of textual, audio, and visual …
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Predictive Analytics for Folk Art Material Requirements
Predictive analytics is a more rational direction of converting material planning to the old folk art manufacturing systems. The use of experiential estimation tends to create shortages in materials, excessive stocking and unviable use of resources further enhanced by seasons and change in demand in the market. To overcome such difficulties, a hybrid forecasting model was created that would have incorporated ARIMA, XGBoost, and LSTM models to for…
Intelligent Systems for Digital Exhibition Design
The study evaluates the evolution and the use of smart systems in designing digital exhibits with the key aspects of how artificial intelligence (AI), machine learning, and immersive technologies can redefine the conventional exhibition models into responsive, interactive, and data-driven cultural experiences. Combining computational intelligence with the human imagination, the study shows that AI-aided curation can boost aesthetic expression, as…
Data Visualization as a Form of Sculptural Art
Data visualization, the interconnection of information and sculptural art is a new paradigm where information moves out of the digital screens and finds space in the physical world to express itself. This paper examines the conceptual, aesthetic and technological systems that allow the data to be physically realized as three dimensional artworks. It investigates how datasets are transformed algorithmically and modeled computationally into forms t…
Music Sentiment Analytics: Understanding Audience Reactions Using Multi-Modal Data From Streaming Platforms
Streaming services are adding more and more user-generated content, which provides us valuable insight on how people feel and how involved they are. Knowing how people feel and react to music may help to make music selection systems, marketing strategies, and outreach efforts to musicians much more efficient. This paper investigates how multi-modal information could be utilised for temper evaluation in song by means of textual, audio, and visual …
Digital Heritage Reconstruction Techniques for Reviving Lost or Damaged Visual Art Traditions
The further reduction of the environment, natural disasters, and human strife have complicated the preservation of the cultural heritage, particularly visual art traditions, even more. Even though effective, there are times when the traditional methods of restoration are not sufficient even in the restoration of highly damaged or lost works. The reconstruction methods of digital heritage have in their turn responded in the form of new solutions t…
Virtual Curation Methods for Organizing Large-Scale International Digital Art Exhibitions
International exhibition of digital art and the rise in worldwide connectivity of cultures have required new strategies of managing large-scale exhibitions. Conventional curation approaches are severely constrained by handling thousands of arts pieces representing different cultural backgrounds, necessitating manual sorting, thematic sorting by hand, and being not very scalable. This study suggests an all-encompassing virtual curation solution th…
Automated Editing Tools for Media Students: A Comparative Study
Purpose: To assess automated editing tools applied in the media education on the basis of technical and pedagogical terms.Methodology: Four categories of automated editing tools were evaluated based on a multi-dimensional model based on the level of automation, usability, creative control, pedagogical compatibility, and workflow efficiency. A student case study based on tasks was added to quantitative scoring.Results: The results show that high a…
Aesthetic Perception and Analysis (3 works) · Analytics (2 works) · Art, Technology, and Culture (2 works) · Cultural heritage (2 works) · Digital art (2 works) · Exhibition (2 works) · Image Processing and 3D Reconstruction (2 works) · 3D Surveying and Cultural Heritage (1 works) · Active listening (1 works) · Architecture and Computational Design (1 works)