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Field
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working with image and video data covering at least selected aspects of data acquisition, quality control, dataset preparation, feature extraction, motion analysis, algorithm validation, or AI model
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algorithms in front-ends, wireline and wireless interfaces, converters, FPGAs, microprocessors, microcontrollers and IP cores throughout all project phases; analysing and profiling the implementation
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have worked with tools, techniques, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related
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, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related areas. In addition, you have demonstrated
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, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related areas. In addition, you have demonstrated
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are met. Undertake these responsibilities in the project: Develop and deploy multimodal AI algorithms for fire, smoke, and hot-work detection by fusing optical, thermal/infrared, LiDAR, RADAR, and gas
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Edge computing and edge analytics frameworks Data acquisition systems and sensor integration Automated control systems and algorithms Cyber-resilient embedded system design Testing methodologies
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device design, algorithms and sensors. The program will be complementary and collaborative with current strengths in computational neuroscience and neuromorphic computing. This position offers excellent
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 months ago
and animals look and move. We develop algorithms to estimate human shape and motion in images, videos, RGB-D sequences, etc. Our approaches define the current state of the art, and we are constantly
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absorption assessment via FDTD using EM field data Detection and localization algorithms of dynamic users using wireless signal parameters and sensor fusion Generation of Digital Twin city model that is able