Sort by
Refine Your Search
-
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
-
applying Natural Language Processing (NLP) algorithms. Knowledge or prior experience in Virtual Reality technologies. Work Plan: The grant aims to develop Agricultural Simulations using Virtual Reality as a
-
Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 17 days ago
, with application to biomedical flows (e.g. microcirculation) it is now intended to develop an improved algorithm for advanced particle tracking using machine learning. The algorithm should be tested in
-
algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
-
algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
-
algorithms to combine information on cardiovascular activity obtained from heart sound signals, electrocardiogram, and photoplethysmography. Investigate the inclusion of prior knowledge about the application
-
algorithms for free-flying robots in microgravity.; • Implement and validate real-time multi-target tracking techniques.; • Validate the algorithms in simulated scenarios, evaluating robustness and accuracy
-
/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Real-time signal analysis algorithms, feature identification, and personalized
-
OF THE WORK PROGRAMME AND TRAINING: 1) Development of workflows and algorithms to complement datasets of connected data spaces, to improve analysis results (forecasting, analysis of financial tools, predictive
-
) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Applying anomaly detection algorithms for streaming network data. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND