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) |