🔭 I'm currently working on:
Building an autoencoder for wireless communications as part of my MiSKS course at FTN. The idea is to model the whole tx/rx chain as a neural network and train it end-to-end instead of designing each block separately.
🤝 I'm looking to collaborate on:
Kaggle competitions, mostly anything involving computer vision or signal processing.
🤝 I'm looking for help with:
Getting better at deep learning. I know the basics of CNNs, RNNs and Transformers but still figuring out when and why to use each one.
🌱 I'm currently learning:
Deep learning architectures and how to actually apply them to real problems, not just run existing code.
💬 Ask me about:
My lip-reading classifier, learned image compression, signal processing, or any of my projects on GitHub.
⚡ Fun fact:
I built a classifier that tells apart Serbian and English just by watching lip movements. No audio at all, 65% accuracy against a 50% baseline.
4th year Telecommunications and Signal Processing student at the Faculty of Technical Sciences, University of Novi Sad.
Popular repositories Loading
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lip-language-classification-mu1
lip-language-classification-mu1 PublicVisual speech (lip-reading) language classification — Serbian vs English — using HOG features, PCA, SVM, MLP and Random Forest. MU1 course project.
Jupyter Notebook 1
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jnd-lic-portraits
jnd-lic-portraits PublicImplementacija ključnih komponenti JND-LIC metode (Pan et al., 2025) zasnovana na CompressAI baseline-u, sa evaluacijom na portretima iz CelebA-HQ
Jupyter Notebook 1
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theremin-cv
theremin-cv PublicHand-tracking digital theremin: webcam + MediaPipe + Python + Arduino Uno
Python 1
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misks-wireless-autoencoder
misks-wireless-autoencoder PublicEnd-to-end PyTorch autoencoder za bezicni prenos preko AWGN kanala (MiSKS, FTN UNS)
MATLAB 1
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