1. Representing visual entities with deep hierarchical and compositional modelsDomen Tabernik, 2021, doctoral dissertation Keywords: compositional hierarchies, histogram of compositions, displaced aggregation units, deep neural networks, visual image recognition, semantic image segmentation, de-blurring Full text (file, 10,00 MB) |
2. Extraction of visible boundaries for cadastral mapping based on UAV imageryBujar Fetai, Krištof Oštir, Mojca Kosmatin Fras, Anka Lisec, 2019, original scientific article Keywords: cadastre, land parcel, land plot, land cadastre, cadastral boundaries, cadastral maps, UAV, image processing, image segmentation, feature extraction, object extraction Full text (file, 11,35 MB) This document has more files! More... |
3. Improved initialization of the EM algorithm for mixture model parameter estimationBranislav Panić, Jernej Klemenc, Marko Nagode, 2020, original scientific article Keywords: mixture model, parameter estimation, EM algorithm, REBMIX algorithm, density estimation, clustering, image segmentation Full text (file, 9,24 MB) This document has more files! More... |
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6. On methods for merging mixture model components suitable for unsupervised image segmentation tasksBranislav Panić, Marko Nagode, Jernej Klemenc, Simon Oman, 2022, original scientific article Keywords: mixture models, parameter estimation, clustering, unsupervised image segmentation Full text (file, 3,79 MB) This document has more files! More... |
7. HaN-SegGašper Podobnik, Primož Strojan, Primož Peterlin, Bulat Ibragimov, Tomaž Vrtovec, 2023, original scientific article Keywords: auto-segmentation, image dataset, computed tomography, magnetic resonance, radiation therapy, head and neck cancer Full text (file, 3,10 MB) This document has more files! More... |
8. Brain Tumor Segmentation on MRI BraTS Data using convolutional neural networks: experimental study and comparisonIrena Dragičević, 2023, master's thesis Keywords: master's theses, radiologic technology, convolutional neural networks, U-Net, BraTS, glioma segmentation, multimodal segmentation, medical image segmentation, machine learning Full text (file, 4,11 MB) |
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10. Combining color and spatial image features for unsupervised image segmentation with mixture modelling and spectral clusteringBranislav Panić, Marko Nagode, Jernej Klemenc, Simon Oman, 2023, original scientific article Keywords: spectral clustering, mixture models, color features, spatial features, image segmentation Full text (file, 1,02 MB) This document has more files! More... |