Prashant Anerao
Biographic Data
| ID | 8967813 |
|---|---|
| NAME | Prashant Anerao |
| GIVEN NAMES | Prashant |
| FAMILY NAME | Anerao |
| SIGNATURE | ANERAO P |
| AFFILIATIONS | International Institute of Information Technology |
| ORCID | 0000-0003-0353-7420 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Digital Archiving of Folk Art Through Machine Learning
Computational problems in the digital preservation of folk art are distinct because of the visual diversities, long tail distributions of motifs, and incomplete meta-data. The proposed paper presents a machine learning-based intelligent system of digital archiving folk art, which incorporates the visual feature learning, the automatic mechanisms of semantic enrichment, and the scaling of the retrieval mechanisms. The method uses both a hybrid con…
Using Holographic Projection Technologies to Create Immersive Visual Experiences in Galleries
The holographic projection technologies have emerged as a ground breaking medium of creating a visual experience that is immersive in contemporary art galleries. The paper focuses on exploring how holography could be incorporated with digital rendering systems to enhance the active involvement of the audience, space perception and storytelling. The research article is an elaborate roadmap of holographic projection system design comprising of hard…
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…
Ai for Regional Art Mapping and Preservation
Artificial intelligence has proven to be a paradigm shift in preservation of cultural heritage and has made it possible to digitize vast portions of heritage, classify intelligently and semantically interconnect regional art forms. The paper introduces a full-fledged AI-based regional art mapping and preservation framework that incorporates various forms of multimodal data visual, textual, and geospatial data in an integrated cultural knowledge f…
Emotion Modeling in Sculpture Design Using Neural Networks
The paper introduces a unified method of designing sculptures on a feeling-sensitive neural network basis. The proposed Emotion-Form Neural Embedding Network (EFNEN) is based on the combination of Convolutional Neural Networks (CNNs) and Graph Neural Networks (GNNs) to learn emotion-related correlations between sculptural form and emotion. The system was trained and tested using a selection of 1,200 annotated 3D models that had both geometric and…
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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…
Ai for Regional Art Mapping and Preservation
Artificial intelligence has proven to be a paradigm shift in preservation of cultural heritage and has made it possible to digitize vast portions of heritage, classify intelligently and semantically interconnect regional art forms. The paper introduces a full-fledged AI-based regional art mapping and preservation framework that incorporates various forms of multimodal data visual, textual, and geospatial data in an integrated cultural knowledge f…
Emotion Modeling in Sculpture Design Using Neural Networks
The paper introduces a unified method of designing sculptures on a feeling-sensitive neural network basis. The proposed Emotion-Form Neural Embedding Network (EFNEN) is based on the combination of Convolutional Neural Networks (CNNs) and Graph Neural Networks (GNNs) to learn emotion-related correlations between sculptural form and emotion. The system was trained and tested using a selection of 1,200 annotated 3D models that had both geometric and…
Digital Archiving of Folk Art Through Machine Learning
Computational problems in the digital preservation of folk art are distinct because of the visual diversities, long tail distributions of motifs, and incomplete meta-data. The proposed paper presents a machine learning-based intelligent system of digital archiving folk art, which incorporates the visual feature learning, the automatic mechanisms of semantic enrichment, and the scaling of the retrieval mechanisms. The method uses both a hybrid con…
Using Holographic Projection Technologies to Create Immersive Visual Experiences in Galleries
The holographic projection technologies have emerged as a ground breaking medium of creating a visual experience that is immersive in contemporary art galleries. The paper focuses on exploring how holography could be incorporated with digital rendering systems to enhance the active involvement of the audience, space perception and storytelling. The research article is an elaborate roadmap of holographic projection system design comprising of hard…
Aesthetic Perception and Analysis (3 works) · Architecture (2 works) · Convolutional neural network (2 works) · Music Technology and Sound Studies (2 works) · Perception (2 works) · Visualization (2 works) · 3D Surveying and Cultural Heritage (1 works) · Accountability (1 works) · Accreditation (1 works) · Advanced Optical Imaging Technologies (1 works)