1. Improving convolutional neural networks performance for image classification using test time augmentationIbrahem Kandel, Mauro Castelli, 2021, original scientific article Keywords: image classification, convolutional neural networks, transfer learning, test time 29 augmentation, deep learning, ensemble learning Full text (file, 1,82 MB) This document has more files! More... |
2. Comparing stacking ensemble techniques to improve musculoskeletal fracture image classificationIbrahem Kandel, Mauro Castelli, Aleš Popovič, 2021, original scientific article Keywords: neuroscience, deep learning, image classification, stacking, ensemble learning, convolutional neural networks, transfer learning, medical images Full text (file, 1,12 MB) This document has more files! More... |
3. Transfer and unsupervised learningLuka Gradišar, Matevž Dolenc, 2023, original scientific article Keywords: clustering, crack detection, data mining, image analysis, transfer learning, unsupervised learning Full text (file, 4,25 MB) This document has more files! More... |
4. Comparative study of first order optimizers for image classification using convolutional neural networks on histopathology imagesIbrahem Kandel, Mauro Castelli, Aleš Popovič, 2020, original scientific article Keywords: image classification, convolutional neural networks, deep learning, medical images, transfer learning, optimizers, neuroscience Full text (file, 573,18 KB) This document has more files! More... |
5. Musculoskeletal images classification for detection of fractures using transfer learningIbrahem Kandel, Mauro Castelli, Aleš Popovič, 2020, original scientific article Keywords: transfer learning, computer vision, convolutional neural networks, image classification, musculoskeletal images, deep learning, medical images, neuroscience Full text (file, 550,23 KB) This document has more files! More... |
6. Style transfer of Aartworks using neural networksENIO KURBEGOVIĆ, 2023, undergraduate thesis Keywords: artificial intelligence, neural networks, neural style transfer, meta networks, image transformation networks, content images, style images Full text (file, 16,90 MB) |
7. Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction modelsLara Dular, Franjo Pernuš, Žiga Špiclin, 2024, original scientific article Keywords: magnetic resonance imaging, brain age prediction, image preprocessing, deep model regression, comparative study, quantitative evaluation, brain age, MRI preprocessing, deep regression models, linear mixed effect models, dataset bias, transfer learning, reproducible research, UK Biobank Full text (file, 4,29 MB) This document has more files! More... |