Nitin Rakesh
Datos Biográficos
| ID | 8115063 |
|---|---|
| NOMBRE | Nitin Rakesh |
| NOMBRES | Nitin |
| APELLIDO | Rakesh |
| FIRMA | RAKESH N |
| AFILIACIONES | Symbiosis International University |
| ORCID | 0000-0002-6400-4954 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAS | 0 |
| OBRAS COMO AUTOR | 2 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2025 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 0 |
Optimizing real-time stereo image retargeting for AR/VR
Real-time stereo image retargeting for augmented reality (AR) and virtual reality (VR) necessitates precise per-pixel depth estimation and ultra-low latency performance on resource-limited edge devices. Current disparity convolutional neural networks (CNNs) and retargeting pipelines are unable to meet these demanding requirements concurrently. This paper presents EASNet, a compact end-to-end framework that unifies geometry-aware proposal generati…
Ai-Driven Music Curation and Visual Culture
Social music curation has turned into a hallmark of AI-powered creative platforms defining the way digital platform forms listening habits and the visual culture, as well as the way to engage with the audience. This paper discusses the connection between AI and music recommendation which applies visual aesthetics to analyse the audience preferences in a modern digital creative ecosystem. The issue being discussed involves the lack of transparency…
Sin obras prominentes en esta página.
Ai-Driven Music Curation and Visual Culture
Social music curation has turned into a hallmark of AI-powered creative platforms defining the way digital platform forms listening habits and the visual culture, as well as the way to engage with the audience. This paper discusses the connection between AI and music recommendation which applies visual aesthetics to analyse the audience preferences in a modern digital creative ecosystem. The issue being discussed involves the lack of transparency…
Optimizing real-time stereo image retargeting for AR/VR
Real-time stereo image retargeting for augmented reality (AR) and virtual reality (VR) necessitates precise per-pixel depth estimation and ultra-low latency performance on resource-limited edge devices. Current disparity convolutional neural networks (CNNs) and retargeting pipelines are unable to meet these demanding requirements concurrently. This paper presents EASNet, a compact end-to-end framework that unifies geometry-aware proposal generati…
Active listening (1 obra) · Advanced Image Processing Techniques (1 obra) · Advanced Vision and Imaging (1 obra) · Aesthetic Perception and Analysis (1 obra) · Digital audio (1 obra) · Edge detection (1 obra) · Enhanced Data Rates for GSM Evolution (1 obra) · Image processing (1 obra) · Image segmentation (1 obra) · Music and Audio Processing (1 obra)