Iason Karakostas

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About

Iason Karakostas is a leading researcher in embedded computer vision and autonomous aerial systems, with a focus on real-time visual perception for Unmanned Aerial Vehicles (UAVs). His most-cited work, "Embedded UAV Real-Time Visual Object Detection and Tracking" (2019, 46 citations), addresses the critical challenge of deploying sophisticated vision algorithms directly on resource-constrained drone platforms. Karakostas’s major contribution lies in bridging the gap between high-performance deep learning models and the limited computational power of embedded systems, enabling UAVs to perform autonomous object detection and tracking without relying on ground-based processing. This work has significant implications for media production, surveillance, and search-and-rescue operations, where real-time, onboard intelligence is essential. Beyond this flagship paper, his research explores efficient neural network architectures and hardware-software co-design for aerial robotics. Karakostas’s impact is evident in the growing adoption of his methodologies in both academic and industrial drone applications, and he is recognized for advancing the practical deployment of AI on edge devices, making autonomous drones smarter, faster, and more reliable in dynamic environments.