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fundamentals of networking. Objectives: To achieve on-device spectrum sensing using on-board sensors of mobile BSs, empowered by embedded deep learning algorithms; to propose an analytical model for the cell
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, LiDAR, AHRS, and other sensors directly on low-power embedded platforms. Where to apply E-mail resurse.umane@upb.ro Requirements Research FieldEngineering » Electronic engineeringEducation LevelMaster
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballots using the STV method. Our first point of
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, enabling energy-efficient, quiet, and long-duration monitoring of ecosystems. The research will integrate novel lightweight perception modalities for robust perching in the wild, agile control algorithms
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encompass a range of microhabitats and environmental gradients characteristic of maritime Antarctica. High-resolution UAV imagery acquired with multispectral, thermal, and hyperspectral sensors will be
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wireless sensor networks as well as research and education within Life Science, smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with
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application will concern multi-sensors based systems for autonomous vehicles embedding AI perception or decision modules. The experiments will rely on embedded platforms available at LCIS, including
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/m/d) Development of soft-sensors connected to particlebased separation models to control flotation processes. Your tasks Develop and implement soft‑sensor concepts for continuous monitoring of ore
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, cargo, harbors etc. Large and deep AI models can be built using these data sets and machine learning, which can be combined with real-time satellite-based AIS data and sensors such as radar and algorithms