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to create accurate cell charging and discharging models. 3. Development of Estimation Algorithms: Create algorithms to accurately estimate the state of charge (SOC) and state of health (SOH) of batteries. 4
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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of the call Past experience in AI algorithms Past experience in Research Projects EVALUATION CRITERIA The selection will be based on the following criteria: Academic record (50%) Past Experience in AI
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layers and data processing ; 2) Development of machine learning algorithms for traffic characterization and damage detection; 3) Development of a toolbox for the automatic data acquisition and
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; develop and validate an astrodynamics-based orbit determination algorithm using TFC, including hybrid solutions with stochastic filters (eg, EKF or UKF); integrate and calibrate optical sensors and develop
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mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering, or neural networks). Non-negative tensor factorization
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, and will have the following specific responsibilities: • Manual annotation of videos (L3 level with bounding boxes) of deep-sea biodiversity to train artificial intelligence (AI) algorithms and feed a
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Using Machine Learning Algorithms (Plasmon-2Detect), ref. COMPETE2030-FEDER-00714300, number of the project - 16004, financed by the European Regional Development Fund (ERDF), with a view to the
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from users and participating academies. They will be responsible for evaluating the performance of personalized training plan recommendation algorithms, predictive models of user evolution, and class
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Objectives: Development and implementation of computer vision and active learning algorithms for sign languages, including (i) a pipeline for the ingestion and extraction of visual gesture features