Reinforcement Learning for Switching of Semiautomated Vehicles Under Uncomfortable Driving Situations

Over the last two decades, autonomous driving has progressed from science fiction to a real possibility and rapidly developing. However, autonomous driving technology has significant weaknesses and is not safe in unexpected conditions. As a result, automobile manufacturers insist that the driver remains in the driver's seat even while the...

HaarCNN: Detection and Recognition of Comic Strip Characters with Deep Learning and Cascade Classifiers

Object detection and recognition is a computer vision problem tackled with techniques such as convolutional neural networks or cascade classifiers. This paper tackles the challenge of using the similar methods in the realm of comics strips characters. We approached the idea of combining cascade classifiers with various convolutional neural...

DilBERT^2: Humor Detection and Sentiment Analysis of Comic Texts Using Fine-Tuned BERT Models

The field of Natural Language Processing (NLP) techniques has progressed rapidly over the recent years. With new advancements in transfer learning and the creation of open-source projects like BERT, solutions and research projects emerged implementing new ideas in a variety of domains, for tasks including text classification or question...

Text-to-Comic Generative Adversarial Network

Drawing and annotating comic illustrations is a complex and difficult process. No existing machine learning algorithms have been developed to create comic illustrations based on descriptions of illustrations, or the dialogue in comics. Moreover, it is not known if a generative adversarial network (GAN) can generate original comics that...

Reinforcement Learning for Switching Control of Semi-automated Vehicles with Driver Fatigue

Automated driving is a rapidly growing technology nowadays. Semi-automated driving is a subpart of automated driving which has multiple driving modes where both driver and automated module can take control. But full safety and comfort guarantees cannot still be given to the drivers. In this project, research has been done to ensure driver safety...

Reinforcement Learning approach for decision-making in driver control shifting for semi-autonomous driving

Semi-autonomous driving innovations aim to bridge the gap to fully autonomous driving by co-operating with human drivers to lead to optimal choices on who should drive in different scenarios by offering different automation levels. However, in the present day, known semi-autonomous driving solutions do not generalise to every complex case of...

Optimizing driving entity switching of semi-automated vehicles under automation degradation

Transitioning to use automated vehicles is a gradual process. Until full automation capabilities are developed there is a need to mediate which driving entity - human or autonomous driving system (ADS) - should be in control depending on the circumstances. This research aims at investigating the switching between manual and automated driving in...

Automated Text-Image Comic Dataset Construction

Comic illustrations and transcriptions form an attractive dataset for several problems, including computer vision tasks, such as recognizing character’s faces, generating new comics, or natural language processing tasks like automated comic translation or detecting emotion in the dialogues. However, despite a large number of comic strips...

Synthesizing Comics via Conditional Generative Adversarial Networks

The creation of comic illustrations is a complex artistic process resulting in a wide variety of styles, each unique to the artist. Conditional image synthesis refers to the generation of de novo images based on certain preconditions. Applying machine learning to conditionally generate novel comics proves an intriguing yet difficult task. This...