Ervin Yohannes

National Central University

Papers

1

Total Citations

8

H-Index

1

About

Ervin Yohannes is a researcher at the forefront of assistive computer vision, dedicated to bridging the gap between advanced AI and real-world accessibility. His work centers on developing intelligent systems that empower visually impaired individuals to navigate and interact with their surroundings autonomously. Yohannes’s most notable contribution is the "Robot Eye" system, which leverages a deep attention network for automatic object detection and recognition. By integrating a ZED stereo camera for depth calculation, his research provides a practical, outdoor navigation aid that guides blind users through complex environments. This work, published in 2020 and garnering 8 citations, addresses persistent challenges in computer vision by focusing on real-time, actionable assistance rather than mere detection. Yohannes’s approach exemplifies a human-centered application of deep learning, where technical innovation directly serves a pressing societal need. His research not only advances the field of assistive robotics but also sets a benchmark for deploying AI in high-stakes, dynamic settings, making him a key figure in the movement toward inclusive technology.

Research Focus

Key Achievements

1
H-Index
1
Papers
8
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Robot Eye: Automatic Object Detection And Recognition Using Deep Attention Network to Assist Blind People
8 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: National Central University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago