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Experience with ROS/2 and perception libraries, including but not limited to - OpenCV, PCL, and Eigen. Deep learning/machine learning for computer vision. Practical applications of classical computer vision and machine learning techniques.
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Hands-on experience in computer vision and deep learning frameworks, e.g., OpenCV, Tensorflow, Keras, Pytorch, and Caffe. Apply and optimize model compression and quantization technique to variety of models in computer vision applications, audio applications, and others.
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Python, MATLAB, Simulink, STK, DOORS, Rhapsody, DXL, JIRA, Excel VBA, OpenCV. Specifically, as a Computer Vision Software Engineer, you will generate synthetic imagery, develop image exploitation algorithms, test and field algorithms to real-time hardware, and work with the navigation team to develop novel concepts for multiple in-space applications.
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Computer Vision and Deep Learning software and techniques (VA/ML, OpenCV, Yolo, Tensorflow, PyTorch) Master's degree specializing in computer vision, machine learning, analytics or closely-related discipline.
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And OpenCV, experience with computer vision and ML on edge / embedded systems, and demonstrated experience taking complex software systems from concept to production. 2+ years of experience working with OpenCV.
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Image processing libraries such as GDAL, OpenCV. Satellite image processing and computer vision applications. GCCRi is looking for a Software Engineer to join our federal team to develop scalable, high-performant cloud-based computer vision systems focused on the automated detection of objects in satellite imagery.
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Experience with machine vision and image processing, and libraries like OpenCV. Integrate new test equipment, motion control hardware, and vision hardware. At Jabil we strive to make ANYTHING POSSIBLE and EVERYTHING BETTER. With over 250,000 diverse, talented and dedicated employees across 100 locations in 30 countries, our vision is to be the most technologically advanced and trusted manufacturing solutions provider.
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4+ years of hands-on experience with data science libraries (Pandas, Matplotlib, OpenCV etc.) - Published research on computer vision, image processing or machine learning. - Strong knowledge of advanced mathematics and 2+ years of experience in feature engineering, computer vision, NLP and/or recommendation engines.
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Experience with popular SLAM libraries and frameworks, such as ROS, OpenCV, PCL, GTSAM, and g2o. Collaborate with cross-functional teams, including software engineers, computer vision experts, and robotics engineers, to integrate SLAM solutions into various projects.
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OpenCV, OpenGL, or Python. Experience in one or more of the following areas: sensor calibration, computer vision system design, computational photography, digital image processing. Humane’s Computer Vision Team is responsible for key technologies enabling our new class of mobile device and services.
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Willing to provide leadership and mentoring for more junior computer vision engineers. + Willing to lead a team of computer vision engineers, either on a temporary or permanent basis. + Work directly with internal and external developers to transition applications into the computer vision platform.
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Please share the candidate's experience and expertise with libraries such as OpenCV, libgphoto, keras/tensorflow. Experience with libraries such as OpenCV, libgphoto, keras/tensorflow. Please share the candidate's experience in working with a) Computer Vision Applications and b) Machine learning skills.
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Solid understanding of computer vision, sensor fusion, probabilistic robotics, and optimization algorithms. Expertise in various SLAM techniques, such as visual SLAM, LiDAR SLAM, visual-inertial SLAM, graph-based SLAM, Kalman filtering, bundle adjustment, structure from motion, etc.
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Experience with computer vision, OpenCV and image processing. A full benefits package is available, including medical, dental, vision, life insurance 2X annual salary, long-term disability, 401K and FSA/HSA accounts.
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As a SLAM Expert, you will play a technical leadership role in developing and implementing state-of-the-art SLAM algorithms and systems to advance our cutting-edge fulfillment technology. Contribute to the development of tools and frameworks to streamline the SLAM development process.
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