Characterising AI Weakness in Detecting Personal Data from Images By Crowds

This thesis looks at how to characterize weaknesses in machine learning models that are used for detecting privacy-sensitive data in images with the help of crowdsourcing. Before we can come up with a method to achieve a goal, we first need to make clear what we consider privacy-sensitive data. We took the General Data Protection Regulation ...

Multimodal information extraction from videos: Automatic creation of highlight clips from political speeches

With the huge amount of data that is collected every day and shared on the internet, many recent studies have focused on methods to make multimedia browsing simple and efficient, investigating techniques for automatic multimedia analysis. This work specifically delves into the case of information extraction from videos, which is still an open...

A Human-Machine Approach to Preserve Privacy in Image Analysis Crowdsourcing Tasks

Modern web information systems use machine learning models to provide personalized user services and experiences. However, machine learning models require annotated data for training, and creating annotated data is done through crowdsourcing tasks. The content used in annotation crowdsourcing tasks like medical records and images might contain...

The impact of image filters on machine classification and human perception of weather conditions

Nowadays with the growth of social media, users upload millions of photos in different platforms online. Researchers in the field of computer vision devote their time and effort to analyze images in order to gain valuable insight. Data<br/>analysis and classification can be impeded by different factors. One of which is the image filters that are...

On the fairness of crowdsourced training data and Machine Learning models for the prediction of subjective properties. The case of sentence toxicity: To be or not to be #$@&%*! toxic? To be or not to be fair?

Training machine learning (ML) models for natural language processing usually requires lots of data that is often acquired through crowdsourcing. In crowdsourcing, crowd workers annotate data samples according to one or more properties, such as the sentiment of a sentence, the violence of a video segment, the aesthetics of an image, ... To...

Quantifying and Predicting Urban Attractiveness with Street-View Data and Convolutional Neural Networks

Analysing attractiveness of places in a region is beneficial to support urban planning and policy making. However, the attractiveness of a place is a subjective and high-level concept which is difficult to quantify. The existing methods rely on traditional surveys which may require high cost and have low scalability. This thesis attempts to...