Thesis code: 20004
Thesis Type: M.Sc. thesis in Machine Learning, Data Science, Computer Science, Mathematics, or equivalent
Research Area: Data Science for Industrial and Societal Application
- Knowledge of Python
- Software development skills
- Basic concepts on data science, concerning data analysis, processing and machine learning
- Basic concepts on image processing
Monitoring and recognizing workers actions is important, especially in areas where machinery is in operation and in motion, or in scenarios that are becoming more and more current: where workers work together with moving robots. For these reasons it is necessary to have systems capable of monitoring the workers in order to guarantee their safety and health. A thesis is proposed where using video cameras placed in work environments, the employee’s clothing is analysed in order to assess whether he wears all the safety equipment provided, and if not, send a warning signal on a wearable device or smartphone. Also, analyse the actions performed and advise if the worker performs actions that are not appropriate.
The objective of this thesis consists in the study and implementation of machine learning algorithms useful for recognizing and report negative actions performed by workers in a video sequence. The proposed algorithms will be trained using a synthetic dataset and open datasets. The candidate will have both the task of creating the dataset and studying and evaluating the best algorithms to apply for the case of study. The candidate is required to implement machine learning algorithms, with the exploratory possibility of deep learning algorithms using popular framework (TensorFlow, PyTorch, Keras, etc..). tools for extracting information from the Grand Theft Auto V graphic engine. The candidate will have both the task of creating the dataset and studying and evaluating the best algorithms to apply for the case of study.
The type of algorithms being studied and tested are to be classified among those of video analysis, with the exploratory possibility of deep learning algorithms using popular framework (TensorFlow, PyTorch, Keras, etc..).
Contact: send a resume with attached the list of exams to firstname.lastname@example.org specifying the thesis code and title.