Anoshan Indreswaran
Papers
1
Total Citations
13
H-Index
1
About
Anoshan Indreswaran is a researcher at the forefront of applied artificial intelligence, with a primary focus on deep learning and computer vision for industrial automation. His work bridges the gap between cutting-edge neural network architectures and real-world logistical challenges, particularly in object detection within complex, dynamic industrial environments. His most cited paper, "Application of open Source Deep Neural Networks for Object Detection in Industrial Environments" (2018, 13 citations), addresses the critical need for perception-controlled robots capable of navigating the optical complexities of factories—such as labeling, damage, and variable lighting. By demonstrating how open-source deep neural networks can be effectively deployed in these settings, Indreswaran’s research has laid foundational groundwork for automating handling steps in logistics, enhancing both flexibility and efficiency. His contributions are particularly notable for tackling the unique visual disturbances that hinder traditional automation, making his work highly relevant for industries seeking robust, adaptable robotic solutions.
Research Focus
Key Achievements
Top Papers
- 1