Thesis Code: 19017
Thesis Type: M.Sc. thesis in Machine Learning, Data Science, Computer Science, Mathematics, or equivalent
Research Area: Data Science for Industrial and Societal Application
Requirements:
- Knowledge of Python
- Software development skills
- Basic concepts on data science, concerning data analysis, processing and machine learning
- Basic concepts on image processing
Description:
Monitoring and recognizing pedestrians’ actions is important, especially in areas where there is a risk of terrorist attacks or that are normally poorly guarded, in order to guarantee safety of the citizens. It is therefore necessary to support the police or other surveillance agencies with intelligent systems. These systems must recognize actions that are considered negative, such as theft, brawl, drug dealing, etc.
The objective of this thesis consists in the study and implementation of machine learning algorithms useful for recognizing and report negative actions performed by pedestrians in a video sequence. The proposed algorithms will be trained using a synthetic dataset and open datasets. This is created with the help of dedicated 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 candidate is required to implement machine learning algorithms, 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 mirko.zaffaroni@linksfoundation.com specifying the thesis code and title.
