4 citations · 8 across the 9 of their papers we have counts for
10 papers · 1 filter
Enhancing Coronary Artery Calcium Scoring via Multi-Organ Segmentation on Non-Contrast Cardiac Computed Tomography
Jakub Nalepa, Tomasz Bartczak, Mariusz Bujny +7
Despite coronary artery calcium scoring being considered a largely solved problem within the realm of medical artificial intelligence, this paper argues that significant improvemen…
Self-Configuring nnU-Nets Detect Clouds in Satellite Images
Bartosz Grabowski, Maciej Ziaja, Michal Kawulok +3
Cloud detection is a pivotal satellite image pre-processing step that can be performed both on the ground and on board a satellite to tag useful images. In the latter case, it can…
Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation
Jakub Nalepa, Lukasz Tulczyjew, Michal Myller +1
Hyperspectral imaging provides detailed information about the scanned objects, as it captures their spectral characteristics within a large number of wavelength bands. Classificati…
Unsupervised Segmentation of Hyperspectral Images Using 3D Convolutional Autoencoders
Jakub Nalepa, Michal Myller, Yasuteru Imai +3
Hyperspectral image analysis has become an important topic widely researched by the remote sensing community. Classification and segmentation of such imagery help understand the un…
Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images
Jakub Nalepa, Michal Myller, Michal Kawulok
Deep learning has established the state of the art in multiple fields, including hyperspectral image analysis. However, training large-capacity learners to segment such imagery req…
On training deep networks for satellite image super-resolution
Michal Kawulok, Szymon Piechaczek, Krzysztof Hrynczenko +3
The capabilities of super-resolution reconstruction (SRR)---techniques for enhancing image spatial resolution---have been recently improved significantly by the use of deep convolu…