Sort by
Refine Your Search
-
planning and identification of strings and modules in the field. Development of a computer vision and machine learning pipeline for the detection, localisation and classification of defects in photovoltaic
-
://www.di.ubi.pt ), under the following conditions: Research Field: Machine Learning/Pattern Recognition Objectives: Unsupervised Incremental Representation Learning for Ground-Based Drones in Dynamic Industrial
-
curricular evaluation purposes, proven skills in programming, preferably Python; machine learning and artificial intelligence; language models and retrieval-augmented generation (RAG); ASR/TTS; diarisation
-
used in connection with models for clinical coding. BINDING LEGISLATION Law 40/2004 of 18th of August (Scientific Research Fellow Status) in its current wording. https://www.fct.pt/wp-content/uploads
-
. Workplan and objectives to be achieved: • Review of the state of the art in Edge Machine Learning; • Creation of a dataset to support postural assessment; • Model deployment in
-
of Artificial Intelligence (30%); iii) knowledge of advanced methods for machine learning, such as online or reinforcement learning (20%). Applicants whose application is scored with a final classification of
-
learning-assisted computational pipeline for the automated detection of point defects in atomic-resolution scanning transmission electron microscopy (STEM) images. Using monolayer MoS₂ as a model system, the
-
that are only partially met by the development of special purpose classical computing units. This has motivated a recent interest in using quantum computing to machine learning tasks, in particular to clustering