Nedumaran Arappal
Papers
1
Total Citations
2
H-Index
1
About
Nedumaran Arappal is a researcher at the forefront of applying soft computing and deep learning techniques to computer vision and image analysis. His work focuses on developing intelligent, fine-tuned models for precise pixel-level labeling in 2D images, a critical task for applications in autonomous systems, medical imaging, and object detection. His most cited paper, "A Soft Computing Based Approach for Pixel Labelling on 2D Images Using Fine Tuned R-CNN" (2023), introduces a novel method that enhances the accuracy of region-based convolutional neural networks through careful parameter optimization and soft computing integration. This contribution addresses key challenges in semantic segmentation, offering a more adaptable and computationally efficient solution. With 2 citations, Arappal’s work is gaining recognition for bridging the gap between traditional soft computing and modern deep learning architectures. His research not only advances theoretical understanding but also provides practical frameworks for real-world image processing tasks, making him a promising voice in the evolving landscape of intelligent visual recognition.
Research Focus
Key Achievements
Top Papers
- 1