Jelena Bratulić's Projects
Laboratory exercises from the course Computer Aided Analysis and Design at Faculty of Electrical Engineering and Computing in 2020/2021
Arhitektura, protokoli i usluge u Webu.
Bachelor thesis "Semantic segmentation of road lanes" under the mentorship of prof. Siniša Šegvić, PhD
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
Laboratory exercises from the course Deep Learning at Faculty of Electrical Engineering and Computing in Academic Year 2020/2021.
Basic framework and cheat sheets for Deep Learning experiments with PyTorch
Laboratory exercises from the course Interactive Computer Graphics at the Faculty of Electrical Engineering and Computing in 2019/2020
My personal repository
Github Page, template forked from academicpages.
Kernel Point Convolution implemented in PyTorch
Laboratory exercises from the course Machine Learning at the Faculty of Electrical Engineering and Computing in 2020/2021
Different loss functions and architectures for MonoDepth tested on KITTI dataset.
Laboratory exercises from the course Advanced Algorithms and Data Structures at Faculty of Electrical Engineering and Computing in 2020/2021
Laboratory exercises from the course Fuzzy, Evolutionary and Neuro-Computing at Faculty of Electrical Engineering and Computing in 2020/2021
Laboratory exercises from the course Advanced Operating Systems at Faculty of Electrical Engineering and Computing in Academic Year 2020/2021
Project from the course Statistical Data Analysis at the Faculty of Electrical Engineering and Computing in 2019/2020.
Evaluation of different architectures for Semantic Segmentation on datasets Camvid and LLAMAS.
Pruning methods tested on different deep models for semantic segmentation.
🔥Urban-scale point cloud dataset (CVPR 2021 & IJCV 2022)
Pytorch framework for doing deep learning on point clouds.
A pytorch pruning toolkit for structured neural network pruning and layer dependency maintaining.
Laboratory exercises from the course Artificial Intelligence at the Faculty of Electrical Engineering and Computing in 2019/2020.
在 oxford hand 数据集上对 YOLOv3 做模型剪枝(network slimming)