Detection of Atmospheric Gravity Waves: Two classification approach - Image classification and meteorological feature classification

With the advent of offshore wind farms, the research into the various phenomenon that affects their performance is vast and detailed. But the effect of a particular phenomenon, atmospheric gravity waves (AGWs), on wind farm performance is limited. AGWs are oscillations of the airflow due to an imbalance in the buoyancy and gravity forces,...

Digital Soil Mapping based on PDFs of Cone Penetration Tests and Vibro Cores using Image Processing and Machine Learning

Digital Soil Mapping (DSM) of soil types in geotechnical project areas is a top priority. These maps are often used in decision making and can have significant consequences related to costs and risks. Usually, these maps are generated by digital soil models that interpolate soil types at known locations. In practice, conventional spatial...

Semantic segmentation of historical photographs of the Antarctica peninsula

A huge archive of historical images of the Antarctica taken by the US Navy between 1940 and 2000 is publicly available. These images have not yet been used for large-scale computer-driven analysis as they were captured with analog cameras. They were only later digitized and contain no semantic information. Most modern deep-learning based...

Large Scale In-Database Machine Learning Using Cloud Native Workflows

During the last decade, the proliferation of smartphones, social media and streaming services has provoked an explosion of multimedia data. This large amount of image and video sources combined with more powerful and inexpensive computational capabilities brought by the cloud computing paradigm has facilitated the rapid growth of new machine...

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...

Inferring roof semantics for more accurate solar potential assessment

Led in cooperation with the company Brink, who provides management and consultation services for construction and real estate sectors, this Synthesis Project aims at automatically deriving meaningful information about buildings. More precisely, the focus is to automatically detect roof obstacles - such as dormers, chimneys, and solar panels - to...

A survey on deep learning in medical image reconstruction

Medical image reconstruction aims to acquire high-quality medical images for clinical usage at minimal cost and risk to the patients. Deep learning and its applications in medical imaging, especially in image reconstruction have received considerable attention in the literature in recent years. This study reviews records obtained...

Interpretable Machine Learning for Biomarker Discovery in Imaging Mass Spectrometry Data

Imaging mass spectrometry (IMS) is a multiplexed chemical imaging technique that enables the spatially targeted molecular mapping of biological samples at cellular resolutions. Within a single experiment, IMS can measure the spatial distribution and relative concentration of thousands of distinct molecular species across the surface of a tissue...

Magnetic Resonance Imaging motion correction in k-space: Detecting, estimating and correcting the bulk motion artifacts in k-space data

Magnetic Resonance Imaging is a widely used technique to obtain images of the interior of the human body for diagnosis and treatment. MRI machines capture the raw signal in spatial frequency domain i.e. k-space and the image is obtained via Fourier transform. The Cartesian acquisition is one of the most commonly used acquisition patterns in MRI...

Evaluating and Improving Large-Scale Machine Learning Frameworks

Given the increasing popularity of Machine Learning, and the ever increasing need to solve larger and more complex learning challenges, it is unsurprising that numerous distributed learning strategies have been brought forward in recent years, along with many large scale Machine Learning frameworks. It is however unclear how well these...

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...

Active Learning in Image Quality Assessment

A world without digital images is unthinkable in this era of information and communication technology. Billions of images are created, shared and ultimately enjoyed by users every day. However, digital images are sensitive to a wide variety of distortions during the delivery mechanism it goes through. Any of the distortions that can arise during...

Scalable machine learning algorithms on a big data infrastructure

Two currently popular topics in computer science are machine learning and big data. Often the two are combined to obtain powerful machines with learning capabilities or high throughput data analysis programs among others. This research analyses which machine learning techniques qualify to be efficiently implemented on a scalable big data...