Extension of Tamura Texture Features for 3D Fluorescence Microscopy. - Tomás Majtner; David Svoboda (3DIMPVT, 2012)

Texture analysis using 3D Gabor features and 3D MPEG-7 Edge Histogram descriptor in fluorescence microscopy. - Tomás Majtner; David Svoboda (IC3D, 2014)

RSURF - The Efficient Texture-Based Descriptor for Fluorescence Microscopy Images of HEP-2 Cells. - Tomás Majtner; Roman Stoklasa; David Svoboda (ICPR, 2014)

Comparison of 3D Texture-Based Image Descriptors in Fluorescence Microscopy. - Tomás Majtner; David Svoboda (IWCIA, 2014)

Efficient k-NN based HEp-2 cells classifier. - Roman Stoklasa; Tomás Majtner; David Svoboda (Pattern Recognit., 2014)

Improving skin lesion segmentation in dermoscopic images by thin artefacts removal methods. - Tomás Majtner; Kristina Lidayova; Sule Yildirim Yayilgan; Jon Yngve Hardeberg (EUVIP, 2016)

Efficient Melanoma Detection Using Texture-Based RSurf Features. - Tomás Majtner; Sule Yildirim Yayilgan; Jon Yngve Hardeberg (ICIAR, 2016)

Combining deep learning and hand-crafted features for skin lesion classification. - Tomás Majtner; Sule Yildirim Yayilgan; Jon Yngve Hardeberg (IPTA, 2016)

Texture analysis of 3D fluorescence microscopy images using RSurf 3D features. - Roman Stoklasa; Tomás Majtner (ISBI, 2016)

Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification. - Tomás Majtner; Buda Bajic; Sule Yildirim; Jon Yngve Hardeberg; Joakim Lindblad; Natasa Sladoje (CoRR, 2018)

Comparison of Deep Learning-Based Recognition Techniques for Medical and Biomedical Images. - Tomás Majtner; Esmaeil S. Nadimi (CAIP (1), 2019)

On the Effectiveness of Generative Adversarial Networks as HEp-2 Image Augmentation Tool. - Tomás Majtner; Buda Bajic; Joakim Lindblad; Natasa Sladoje; Victoria Blanes-Vidal; Esmaeil S. Nadimi (SCIA, 2019)

Validation of electron microscopy initial models via small angle X-ray scattering curves. - Amaya Jiménez; Slavica Jonic; Tomás Majtner; Joaquín Otón; Jose Luis Vilas; David Maluenda; Javier Mota; Erney Ramírez-Aportela; Marta Martínez; Yaiza Rancel; Joan Segura; Rubén Sánchez García; et al. (Bioinform., 2019)

Optimised deep learning features for improved melanoma detection. - Tomás Majtner; Sule Yildirim Yayilgan; Jon Yngve Hardeberg (Multim. Tools Appl., 2019)

Non-invasive detection of diabetic complications via pattern analysis of temporal facial colour variations. - Tomás Majtner; Esmaeil S. Nadimi; Knud Bonnet Yderstraede; Victoria Blanes-Vidal (Comput. Methods Programs Biomed., 2020)

Generalised deep learning framework for HEp-2 cell recognition using local binary pattern maps. - Buda Bajic; Tomás Majtner; Joakim Lindblad; Natasa Sladoje (IET Image Process., 2020)

HEp-2 Cell Image Recognition with Transferable Cross-Dataset Synthetic Samples. - Tomás Majtner (CAIP (1), 2021)

Texture-Based Image Transformations for Improved Deep Learning Classification. - Tomás Majtner; Buda Bajic; Jürgen Herp (CIARP, 2021)