Deep reinforcement learning has demonstrated its capability to solve a diverse array of challenging problems, which were not able to solve previously. It has been able to achieve human-level performance in Atari 2600 games and it has shown great p...
The focus of this thesis is on automation in road asset inspection using deep neural networks. Even though some progress has been made in automation of data collection and condition assessment, the amount of manual operation and the cost of road i...
Feedback driven deep reinforcement learning methodologies are widely favoured approaches to solving artificial intelligence problems. The algorithms navigate complex decision-making tasks without manual state space engineering. Notable problems co...
To automatically classify biological images, machine learning techniques have been widely used to train the classifiers from labeled images. For a new category of biological object, a tedious and expensive labeling process is needed from a human e...
