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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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clothoid-specific algorithms that generate a speed profile that takes into account the characteristics and properties of the applications, applied to the movement of human arms/hands, human locomotion, and
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; T2: State-of-the-art review and model testing; T3: Development of algorithms for information extraction; T4: Algorithm testing and validation; T5: Preparation of reports, presentations, and other
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algorithms; Minimum requirements: - experience with cross-platform mobile development frameworks (Ionic); - experience in software development using the Python programming language. 5. EVALUATION
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to explore new optimizations, such as data deduplication, support for multi tenancy, and new scheduling algorithms. These optimizations should be implemented and integrated into the platform.; Implementation
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selection of sensors and their respective lighting to be adopted.; 3. Study and development of algorithms for detecting inconsistencies.; 4. Study and implementation of operator interfaces.; 5. Assembly and
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 16 days ago
management from water and energy sensors; Development of algorithms to improve data collection pipelines from water and energy sensors; Analysis of water and energy datasets using AI techniques, including
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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available under the following conditions: OBJECTIVES | FUNCTIONS Development and evaluation of machine unlearning algorithms for speech foundation models, including: - Selection and preparation of models and