Ashlyn Selena DSouza
Birla Institute of Technology and Science, Pilani - Dubai Campus
Papers
1
Total Citations
16
H-Index
1
About
Ashlyn Selena DSouza is a rising researcher at the intersection of computer vision, deep learning, and intelligent manufacturing. Her work focuses on overcoming the limitations of traditional image processing in industrial automation, particularly in weld seam identification and robotic guidance. In her most cited paper, "GAN-Based Image Dehazing for Intelligent Weld Shape Classification and Tracing Using Deep Learning" (2022, 16 citations), DSouza tackles a critical challenge: the degradation of visual data caused by arc light, weld fumes, and complex backgrounds. By integrating Generative Adversarial Networks (GANs) for image dehazing with deep learning-based shape classification, she enables more robust and automated weld seam tracing—reducing reliance on slow, manual edge detection. This work demonstrates her ability to apply advanced AI techniques to real-world industrial problems, improving both accuracy and efficiency. With her research bridging the gap between theoretical computer vision and practical robotics, DSouza is contributing to the next generation of smart manufacturing systems. Her growing citation count reflects the relevance of her work to both academic researchers and industry practitioners seeking to automate complex visual tasks in harsh environments.
Research Focus
Key Achievements
Top Papers
- 1