Vedran Bilas
Papers
2
Total Citations
55
H-Index
2
About
Vedran Bilas is a leading researcher in electromagnetic sensing and detection technologies, with a primary focus on advancing methods for buried target discrimination and classification. His major contributions lie in developing robust, model-based algorithms that use electromagnetic induction (EMI) data to distinguish hazardous metallic objects—such as landmines and unexploded ordnance—from benign metallic clutter. His most-cited work (2016, 49 citations) introduces a novel approach for estimating the shape of metal targets from time-domain EMI signals, significantly improving the accuracy and reliability of subsurface threat identification. Bilas also pioneered a model-based classification algorithm (2015, 6 citations) that integrates spatial and temporal features of metal detector responses, enabling autonomous robotic systems to detect landmines with greater precision. His research has direct implications for humanitarian demining, environmental remediation, and security applications. With a strong track record in sensor design, signal processing, and field robotics, Bilas continues to shape the future of intelligent electromagnetic sensing, making critical strides toward safer, faster, and more effective subsurface detection systems.
Research Focus
Key Achievements
Top Papers
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