Na FER-u postoji više zaposlenika s imenom
Weakly Supervised Training of Universal Visual Concepts for Multi-domain Semantic Segmentation
Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data
DenseHybrid: Hybrid Anomaly Detection for Dense Open-Set Recognition
Dense open-set recognition based on training with noisy negative images
Automatic universal taxonomies for multi-domain semantic segmentation
Multi-domain semantic segmentation with overlapping labels
Dense open-set recognition with synthetic outliers generated by Real NVP
Multi-domain semantic segmentation with pyramidal fusion
Traffic Scene Classification on a Representation Budget
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift
In Defense of Pre-Trained ImageNet Architectures for Real-Time Semantic Segmentation of Road-Driving Images
Convolutional Models for Segmentation and Localization
Nastava
Sveučilišni preddiplomski
- Oblikovni obrasci u programiranju (Auditorne vježbe, Laboratorijske vježbe, Auditorne vježbe, Laboratorijske vježbe)
- Arhitektura računala 2 (Laboratorijske vježbe, Laboratorijske vježbe)
Sveučilišni diplomski
- Duboko učenje 1 (Laboratorijske vježbe)
- Duboko učenje 1 (Laboratorijske vježbe)