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Scene Understanding Detection and Identification of Objects (SSUDIO) project. The purpose of this project is to develop scene understanding from 3D scans of ships by applying machine learning/computer
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for developing novel 3D scene understanding methods. We will first aim at representing individual objects with 3D primitives given partial point clouds in an unsupervised way. This will be done by leveraging our
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scenery—a mosaic of history, arts, and a vibrant tech scene. We invite you to join a community that cherishes outdoor adventure as much as forward-thinking growth, an exceptional setting for both career and
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of field measurements with 3D Doppler-LIDAR and ultrasonic anemometers, high-fidelity CFD simulations, and controlled experiments. AI-supported methods for spatiotemporal prediction of microclimatic
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adaptive Kalman filters and transformer architectures. Integration of object detection and landmark recognition with 3D city models may enable semantic awareness for navigation. Efficient map compression and
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/Unreal), 3D character/scene design and animation, interactive storytelling, gameplay mechanics, prototyping, and user experience design. Proficiency in English is required. English is the medium
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Dipartimento di Ingegneria dell'Informazione - Università degli Studi di Padova | Italy | about 2 months ago
at the timely recognition of errors and anomalies. In particular, a computer vision system based on a network of cameras will be developed for the real-time 3D reconstruction and understanding under
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creating original computer-generated imagery to explore how lighting and rendering shape the emotional ambience of a scene. This learning forms the foundation for further studies in Visual Effects and 3D
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. Integrate radiological variables into the 3D map of the accident scene. Carry out tests on the operation of the communication and visualization system in real time. Calibrate the detector-drone assembly
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study on camera pose estimation using deep learning-based methods, ii) identification of scenarios to be used as case studies, iii) data collection and construction of 3D models of the involved scenes, iv