mihajlo-ostojic

agent-project

attention-is-all-you-need-transformer-implementation-pytorch

This project is an implementation of the transformer model introduced in the research paper "Attention is All You Need".

chat-application

company-card-image-reading-OCR-with-pytesseract-opencv

Computer vision project that focuses on reading business card images and extracting relevant information using Optical Character Recognition (OCR) techniques. The project uses the Python programming language and several popular libraries for image processing, including PyTesseract and OpenCV.

DatingApp

facial-emotion-recognition-with-HOG-neural-networks

This project aims to recognize facial emotions using machine learning techniques. The input images are preprocessed using Histogram of Gradients (HoG) feature extraction technique to extract facial features. The extracted features are then fed into a neural network for classification of facial emotions.

image-classification-with-cnn-fashionMnist-pytorch

This project uses Convolutional Neural Networks (CNN) and PyTorch to perform image classification on the Fashion-MNIST dataset.

ML-code-smell-detection-with-active-learning

This project uses machine learning models to detect code smells in software projects, with an active learning technique to improve model performance.

sbnz-projekat

test

mihajlo-ostojic/agent-project

mihajlo-ostojic/attention-is-all-you-need-transformer-implementation-pytorch

This project is an implementation of the transformer model introduced in the research paper "Attention is All You Need".

mihajlo-ostojic/chat-application

mihajlo-ostojic/company-card-image-reading-OCR-with-pytesseract-opencv

Computer vision project that focuses on reading business card images and extracting relevant information using Optical Character Recognition (OCR) techniques. The project uses the Python programming language and several popular libraries for image processing, including PyTesseract and OpenCV.

mihajlo-ostojic/DatingApp

mihajlo-ostojic/facial-emotion-recognition-with-HOG-neural-networks

This project aims to recognize facial emotions using machine learning techniques. The input images are preprocessed using Histogram of Gradients (HoG) feature extraction technique to extract facial features. The extracted features are then fed into a neural network for classification of facial emotions.

mihajlo-ostojic/image-classification-with-cnn-fashionMnist-pytorch

This project uses Convolutional Neural Networks (CNN) and PyTorch to perform image classification on the Fashion-MNIST dataset.

mihajlo-ostojic/ML-code-smell-detection-with-active-learning

This project uses machine learning models to detect code smells in software projects, with an active learning technique to improve model performance.

mihajlo-ostojic/sbnz-projekat

mihajlo-ostojic/test

mihajlo-ostojic/transfer-learning-with-EfficientNet-B0-on-Food101-Dataset

mihajlo-ostojic/visual-transformer-paper-replication-with-pytorch

This repository contains code for implementing the Visual Transformer (ViT) model introduced in the research paper "An Image is worth 16x16 words". The model in implemented with pytorch.