Sadhana Sargam
Biographic Data
| ID | 8967833 |
|---|---|
| NAME | Sadhana Sargam |
| GIVEN NAMES | Sadhana |
| FAMILY NAME | Sargam |
| SIGNATURE | SARGAM S |
| AFFILIATIONS | Noida International University |
| VERIFIED | No |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Predictive Analytics in Arts Education Management
The growing sophistication of arts education management, which is created by the variety of learning trajectories, subjective evaluation practices, and production of multimodal creative products, is the reason why the decision-support mechanisms developed beyond the conventional descriptive analytics. The given paper presents an IEEE-based predictive analytics framework adapted to arts education management with the incorporation of heterogeneous …
Emotion-Aware Tutoring Systems for Performing Arts
Digital performing arts education Emotion-aware tutoring systems are a new development in the field of digital performing arts, which combines the concept of affective computing with multimodal learning analytics to improve the growth of expressive skills. Conventional online training systems have been emphasizing more on technical accuracy pitch accuracy, movement accuracy or dialogue accuracy but have failed to consider the emotional shades req…
Art Market Predictions Through Deep Learning
The international art market lends complex dynamics that interact with aesthetic perception, the cycle of economic activities and the mood of the investor, making it a difficult task to forecast prices. The paper presents a deep learning architecture that combines visual, contextual, and temporal data to predict the valuations of artworks with further accuracy. The study proposes a data engineering pipeline that is multimodal that includes curate…
Deep Learning Models for Choreography Generation
Due to the rapid development of deep learning, the new opportunities of computational production of human movement have been opened, especially in the field of dance choreography. The paper discusses deep learning choreography generators that combine movement information, music framework, and time in order to create expressive and sensible sequences of dances. Conventional choreography models tend to have a handmade regulation or professionalized…
Predictive Maintenance for Interactive Art Installations
Interactive art installations are a combination of creativity and technology to interact with audiences by responding to environmental and user stimulation. The challenge is however, keeping these systems up to date since they are installed with sophisticated hardware and software modules which may fail or deteriorate at any time. Conventional maintenance approaches such as reactive or planned maintenance are usually accompanied by downtimes and …
Intelligent Assessment Systems in Digital Art Education
During educational assessment, the Artificial Intelligence (AI) has become the new way of assessing creativity and skill, specifically in the teaching of digital art. This article discusses the development and application of Intelligent Assessment Systems (IAS) that have the capability of assessing artistic outputs objectively and holistically. Conventional approaches to art assessment are more subjective and thus hard to scale and be consistent.…
Sound Emotion Mapping Using Deep Learning
Emotion recognition from sound is an important area of affective computing where machines can use vocal cues as an indication of human emotions for empathic and adaptive interactions. Traditional methods based on handcrafted acoustic features like MFCCs and LPC are restricted in terms of nonlinear and context-dependent emotional dynamics and mostly suffer from speaker and recording condition variations. To solve these issues, in this study the de…
Ai for Preserving Indigenous Folk Art Patterns
The indigenous folk art traditions represent centuries of cultural wisdom, community belonging, symbolism, and craftsmanship which are specific to a certain region. The continuity of these visual heritage systems is however endangered by fast urbanization, erosion of artisanal transmission and little digital documentation. The presented paper is an AI-based model of the preservation of indigenous folk art patterns by creating systems of data, dev…
No prominent works on this page.
Emotion-Aware Tutoring Systems for Performing Arts
Digital performing arts education Emotion-aware tutoring systems are a new development in the field of digital performing arts, which combines the concept of affective computing with multimodal learning analytics to improve the growth of expressive skills. Conventional online training systems have been emphasizing more on technical accuracy pitch accuracy, movement accuracy or dialogue accuracy but have failed to consider the emotional shades req…
Art Market Predictions Through Deep Learning
The international art market lends complex dynamics that interact with aesthetic perception, the cycle of economic activities and the mood of the investor, making it a difficult task to forecast prices. The paper presents a deep learning architecture that combines visual, contextual, and temporal data to predict the valuations of artworks with further accuracy. The study proposes a data engineering pipeline that is multimodal that includes curate…
Deep Learning Models for Choreography Generation
Due to the rapid development of deep learning, the new opportunities of computational production of human movement have been opened, especially in the field of dance choreography. The paper discusses deep learning choreography generators that combine movement information, music framework, and time in order to create expressive and sensible sequences of dances. Conventional choreography models tend to have a handmade regulation or professionalized…
Predictive Maintenance for Interactive Art Installations
Interactive art installations are a combination of creativity and technology to interact with audiences by responding to environmental and user stimulation. The challenge is however, keeping these systems up to date since they are installed with sophisticated hardware and software modules which may fail or deteriorate at any time. Conventional maintenance approaches such as reactive or planned maintenance are usually accompanied by downtimes and …
Intelligent Assessment Systems in Digital Art Education
During educational assessment, the Artificial Intelligence (AI) has become the new way of assessing creativity and skill, specifically in the teaching of digital art. This article discusses the development and application of Intelligent Assessment Systems (IAS) that have the capability of assessing artistic outputs objectively and holistically. Conventional approaches to art assessment are more subjective and thus hard to scale and be consistent.…
Sound Emotion Mapping Using Deep Learning
Emotion recognition from sound is an important area of affective computing where machines can use vocal cues as an indication of human emotions for empathic and adaptive interactions. Traditional methods based on handcrafted acoustic features like MFCCs and LPC are restricted in terms of nonlinear and context-dependent emotional dynamics and mostly suffer from speaker and recording condition variations. To solve these issues, in this study the de…
Ai for Preserving Indigenous Folk Art Patterns
The indigenous folk art traditions represent centuries of cultural wisdom, community belonging, symbolism, and craftsmanship which are specific to a certain region. The continuity of these visual heritage systems is however endangered by fast urbanization, erosion of artisanal transmission and little digital documentation. The presented paper is an AI-based model of the preservation of indigenous folk art patterns by creating systems of data, dev…
Predictive Analytics in Arts Education Management
The growing sophistication of arts education management, which is created by the variety of learning trajectories, subjective evaluation practices, and production of multimodal creative products, is the reason why the decision-support mechanisms developed beyond the conventional descriptive analytics. The given paper presents an IEEE-based predictive analytics framework adapted to arts education management with the incorporation of heterogeneous …
Convolutional neural network (4 works) · Aesthetic Perception and Analysis (3 works) · Deep learning (3 works) · Visualization (3 works) · Art, Technology, and Culture (2 works) · Artificial neural network (2 works) · Diverse Music Education Insights (2 works) · Human Motion and Animation (2 works) · Neuroscience and Music Perception (2 works) · Affective Computing (1 works)