1 citations · 2 across the 6 of their papers we have counts for
6 papers
Semantic Segmentation-Driven Image-Level Diagnosis of Liver Cancers in Hematoxylin and Eosin Histopathology Images
Ivica Kopriva, Dario Sitnik, Arijana Pacic +3
As hematoxylin & eosin (H&E) staining constitutes the primary entry point in routine diagnostic workflows, computer-aided diagnosis from whole-slide H&E images is of particular cli…
Label-independent hyperparameter-free self-supervised single-view deep subspace clustering
Lovro Sindicic, Ivica Kopriva
Deep subspace clustering (DSC) algorithms face several challenges that hinder their widespread adoption across variois application domains. First, clustering quality is typically a…
Interpretable label-free self-guided subspace clustering
Ivica Kopriva
Majority subspace clustering (SC) algorithms depend on one or more hyperparameters that need to be carefully tuned for the SC algorithms to achieve high clustering performance. Hyp…
A Hyperspectral Imaging Dataset and Methodology for Intraoperative Pixel-Wise Classification of Metastatic Colon Cancer in the Liver
Ivica Kopriva, Dario Sitnik, Laura-Isabelle Dion-Bertrand +3
Hyperspectral imaging (HSI) holds significant potential for transforming the field of computational pathology. However, there is currently a shortage of pixel-wise annotated HSI da…
Subspace Clustering in Wavelet Packets Domain
Ivica Kopriva, Damir Sersic
Subspace clustering (SC) algorithms utilize the union of subspaces model to cluster data points according to the subspaces from which they are drawn. To better address separability…
Multilayer Graph Approach to Deep Subspace Clustering
Lovro Sindičić, Ivica Kopriva
Deep subspace clustering (DSC) networks based on self-expressive model learn representation matrix, often implemented in terms of fully connected network, in the embedded space. Af…