Browsing Fakultet for informasjonsteknologi og elektroteknikk (IE) by Subject "Datateknologi, Kunstig intelligens"
Now showing items 21-40 of 55
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Deep Visual Domain Adaptation: - From Synthetic Data to the Real World
(Master thesis, 2018)In the field of computer vision, the increasing use of convolutional neural networks (CNN) fuels the need for more and more labeled training data. Synthetic data generated from computer graphics represent an alternative ... -
Detecting and Localizing Cell Nuclei in Medical Images.
(Master thesis, 2018)In this master thesis we have adapted and implemented Mask R-CNN to the task of detecting and localizing nuclei in medical imaging. Mask R-CNN, which does instance segmentation, was chosen as the architecture to implement, ... -
Developmental Boolean Network as a Model for Electrical Activity in Living Neural Cultures
(Master thesis, 2018)Technological advancement through the last century have made it possible to not only culture neurons in vitro (in glass outside the body), but also to a certain degree record and control their development. Micro-electrode ... -
Distant Supervision and Sentiment Embeddings for Ternary Twitter Sentiment Analysis
(Master thesis, 2017)Tang et al. (2014) acknowledged the context-based word embeddings inability to dis-criminate between words with opposite sentiments that appear in similar contexts. Anexample is the words good and bad two opposites ... -
End-to-end steering angle prediction and object detection using convolutional neural networks
(Master thesis, 2017)Artificial neural networks have enabled a new generation of autonomous vehicles. Public datasets can possibly be used to build networks capable of predicting steering angles and detect objects for self-driving vehicles. ... -
End-to-End Steering Angle Prediction for Autonomous Vehicles
(Master thesis, 2018)In recent years, convolutional neural networks (CNNs) have been applied to several autonomous driving tasks in an end-to-end manner with promising results. As these kinds of systems are given the freedom to self-optimise ... -
Ensuring and Preserving the Privacy of Individuals with a Decentralized Data Marketplace
(Master thesis, 2018)Corporations collect more data about their users than ever. They leave no room for negotiation in their Terms of Service . GDPR, a new EU regulation concerning data ownership, amends this somewhat, but the users are still ... -
Feature Analysis of Supervised Machine Learning Models in IDE-Based Learning Analytics - Exploring the use of correlation coefficients and p-values as feature utility measures through estimating student performance in an introductory programming course
(Master thesis, 2018)Due to the recent proliferation of large datasets collected from human behavior in digital environments, IDE-based learning analytics using supervised learning has emerged as a scientific field. However, due to its novelty, ... -
Guiding the training of Generative Adversarial Networks
(Master thesis, 2017)Image generation with Artificial Neural Networks (ANNs) has been popular in the last few years by using the knowledge about objects and structures to generate dreamlike images, applying smart filters or making images appear ... -
Human-Computer Collaboration for Faster Document Comparison
(Master thesis, 2017)The amount of data in the world is increasing rapidly. One common operation on large datasets is one-to-all comparison, where the goal is to compare one object to all the other objects in the set. This thesis investigates ... -
Implementing a System of Continuous Experimentation in a Software Startup - A participatory action research study
(Master thesis, 2018)By nature, startups face a variety of challenges that well established companies do not. They are newly created companies with no operating history, very limited resources, and they work in an environment that is uncertain, ... -
Improving User Experience of Indoor Maps Through Merging of Rooms
(Master thesis, 2017)The field of indoor map representation is an emerging field of research, contrary to outdoor maps, which has been under research for decades. A lot of focus in indoor maps has been on indoor positioning. However, map ... -
Infant Body Part Tracking in Videos Using Deep Learning - Facilitating Early Detection of Cerebral Palsy
(Master thesis, 2018)The breakthrough of Artificial Intelligence with the advent of Deep Learning has opened paths beyond what have earlier been explored. Within the medical domain, there are potentials to improve how problems are addressed ... -
Inter-/Intra-session Recurrent Neural Network for Session-based Recommender Systems
(Master thesis, 2017)Recommender systems are useful to users of a service and to the company offering the service. Good recommendations can help users find what they are looking for faster, and they can help users discover new content. For ... -
Inter-Session Temporal Modeling in Session-Based Recommendation using Hierarchical Recurrent Neural Networks
(Master thesis, 2018)Recommendation has been a highly relevant and lucrative field of expertise for quite some time. Since the end of the last millennium, session-based recommendation has emerged as an increasingly applicable branch of ... -
Intrinsic Motivation from Distributional Reinforcement Learning
(Master thesis, 2018)Reinforcement learning is learning to behave optimally with respect to an external observer through interactions with an environment. An agent re- peatedly tries to accomplish a goal, each trial yielding some more infor- mation ... -
Knowledge Base Acceleration Using Features Inspired by Collaborative Filtering
(Master thesis, 2017)Most of us use knowledge bases every day, whether it is Wikipedia, Netflix, an online newspaper or a dictionary. These knowledge bases contain both timeless and up-to-date information and must be updated continuously. A ... -
Knowledge exploration in public linked data ontologies
(Master thesis, 2017)The internet is constantly expanding across millions of web pages. Using the internet effectively is a hard skill to learn both for humans and machines. The Semantic Web is an attempt to standardize the data across the web ... -
Learning event-driven time series with phased recurrent neural networks
(Master thesis, 2018)We explore machine learning algorithms for time series data, particularly recurrent neural networks. For us, the most interesting methods are ones for handling long duration time series, where the sampling of data channels ... -
Multiobjective Evolutionary Surgery Scheduling under Uncertainty
(Master thesis, 2018)Surgery scheduling is the task of allocating resources to surgical procedures over time. Because hospitals are dynamic environments governed by uncertainty, difficult priorities and careful coordination of scarce resources, ...