Adithya K. Krishna
Papers
1
Total Citations
3
H-Index
1
About
Adithya K. Krishna is a researcher advancing the frontiers of efficient deep learning for real-time video processing. His primary focus lies in developing lightweight, high-performance neural network architectures that bridge the gap between traditional algorithms and computationally heavy deep learning models. Krishna’s most notable contribution is **RepAr-Net**, a novel framework that integrates re-parameterized encoders with attentive feature arsenals to achieve fast, high-quality video denoising. This work directly addresses a critical bottleneck in fields like mobile robotics, satellite television, and surveillance, where real-time performance is essential but deep learning models are often too large or slow. By demonstrating that carefully designed, compact architectures can rival or surpass conventional methods, Krishna’s research paves the way for deploying advanced AI in resource-constrained environments. With his work already garnering citations and attention, he is establishing himself as a key voice in making state-of-the-art computer vision practical for real-world, latency-sensitive applications.
Research Focus
Key Achievements
Top Papers
- 1