Fiseha B. Tesema
University of Electronic Science and Technology of China, Zhejiang Lab
Papers
2
Total Citations
10
H-Index
2
About
Fiseha B. Tesema is a researcher at the intersection of computer vision and human-robot interaction, whose work advances how machines perceive and engage with people in dynamic environments. His primary research areas include pedestrian detection, multi-scale feature fusion, and addressee detection in mixed human-human and human-robot settings. Tesema’s most cited paper, “Feature Fusing of Feature Pyramid Network for Multi-Scale Pedestrian Detection” (2018, 7 citations), tackles a critical challenge in autonomous driving and intelligent surveillance—accurately detecting pedestrians of varying sizes within a single image. By enhancing feature pyramid networks, his work improves the reliability of real-world vision systems. More recently, Tesema has pioneered deep learning frameworks for addressee detection, as seen in his 2023 paper (3 citations), which enables robots to discern whether they are being spoken to by analyzing facial and audio cues. This contribution is vital for seamless human-robot collaboration, moving beyond constrained meeting-room scenarios to more natural, mixed interactions. His research demonstrates a clear trajectory from foundational object detection to socially aware robotics, positioning him as an emerging voice in creating perceptive, context-aware autonomous systems.
Research Focus
Key Achievements
Top Papers
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