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Guy Kabiri's Projects

coffeeshop icon coffeeshop

Final project in C++ course (without using STL and templates).

cuboids-shearsort-mpi icon cuboids-shearsort-mpi

The Shearsort algorithm is implemented using Odd-Even sorting. In this implementation, C is used along with MPI.

embedded-systems-lab1 icon embedded-systems-lab1

A lab as part of the 'Embedded Systems' course. Using switches to control LEDs and generate sound.

embedded-systems-lab2 icon embedded-systems-lab2

A continue lab to 'Lab1' as part of the 'Embedded Systems' course. Using switches to control LEDs and generate sound, and controlling the LCD.

embedded-systems-lab3 icon embedded-systems-lab3

A lab as part of the 'Embedded Systems' course. Program a new characters into the RAM and display it on the LCD.

face-mask-detection icon face-mask-detection

Object detection exercise for the Neural Networks for Computer Vision course. Using stratified KFold for data with multiple labels and instances, and self-implementation of mAP with multiple configurations.

four-in-a-row icon four-in-a-row

Four-in-a-Row game for a university course. Written in Python, using Tkinter and pyGame. Includes client-server communication over sockets and a multi-process logger with a listener.

image-caption icon image-caption

Exercise on captioning images in the Neural Networks for Computer Vision course. Using the Flickr8K dataset, and simple encoder-decoder architecture. Evaluation based on Cross-Entropy loss and 4-gram Bleu score.

language_models icon language_models

Keras implementations of three language models: character-level RNN, word-level RNN and Sentence VAE (Bowman, Vilnis et al 2016).

parallel-sequence-alignment icon parallel-sequence-alignment

Parallel sequence alignment program that finds the optimal mutation in one sequence of the other. Parallelizes CPU and GPU using OpenMP and CUDA, and communicates with multiple computers using MPI.

plant-pathology-competition icon plant-pathology-competition

Kaggle's plant disease image classification competition. Finetuning pre-trained CNN models, loss functions, and optimizers in order to achieve better results.

video-classification icon video-classification

Video classification exercise using UCF101 data for training an early-fusion and SlowFast architecture model, both using the PyTorch Lightning framework.

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