Anuja Abhijit Phadke
Biographic Data
| ID | 10127341 |
|---|---|
| NAME | Anuja Abhijit Phadke |
| GIVEN NAMES | Anuja Abhijit |
| FAMILY NAME | Phadke |
| SIGNATURE | PHADKE A A |
| AFFILIATIONS | International Institute of Information Technology |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Predictive Modeling for Printing Ink Consumption
In the current printing industries, precise forecasting of printing ink patterns is the key to cost reduction, inventory control, and environmentally friendly functioning. Conventional methods of estimation are based on coverage assumptions, which are always static and operator experience which frequently results in wastage of ink, delay in production and erratic quality. The paper provides an in-depth predictive modelling platform of ink consump…
Machine Learning for Color Optimization in Printing
The optimization of colors in printing has been a subject that is more than ever becoming a critical topic because industries are increasingly demanding greater precision, consistency and efficiency in printing on various substrates and equipment. Conventional color management methods are dependent on manual calibration, ICC profiling and deterministic models which sometimes do not cope with nonlinear device operation, ink substrate interactions …
Smart Sensors and Ai in Musical Instrument Learning
The combination of artificial intelligence (AI) and smart sensor technologies is transforming the musical instrument learning industry by allowing the accurate analysis of performance based on the data. In this paper, the author will discuss the importance of multi-modal sensors (such as motion, pressure, acoustic sensor, and biometric sensor) to capture subtle elements of playing behavior and turn it into actionable data. Through the strategic p…
No prominent works on this page.
Predictive Modeling for Printing Ink Consumption
In the current printing industries, precise forecasting of printing ink patterns is the key to cost reduction, inventory control, and environmentally friendly functioning. Conventional methods of estimation are based on coverage assumptions, which are always static and operator experience which frequently results in wastage of ink, delay in production and erratic quality. The paper provides an in-depth predictive modelling platform of ink consump…
Machine Learning for Color Optimization in Printing
The optimization of colors in printing has been a subject that is more than ever becoming a critical topic because industries are increasingly demanding greater precision, consistency and efficiency in printing on various substrates and equipment. Conventional color management methods are dependent on manual calibration, ICC profiling and deterministic models which sometimes do not cope with nonlinear device operation, ink substrate interactions …
Smart Sensors and Ai in Musical Instrument Learning
The combination of artificial intelligence (AI) and smart sensor technologies is transforming the musical instrument learning industry by allowing the accurate analysis of performance based on the data. In this paper, the author will discuss the importance of multi-modal sensors (such as motion, pressure, acoustic sensor, and biometric sensor) to capture subtle elements of playing behavior and turn it into actionable data. Through the strategic p…
Color Science and Applications (2 works) · Analytics (1 works) · Artificial neural network (1 works) · Biometrics (1 works) · Color management (1 works) · Color perception and design (1 works) · Deep learning (1 works) · Digital printing (1 works) · Diverse Music Education Insights (1 works) · Generalization (1 works)