AlaaAnani/Minesweepers-Shielded-Arduino

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Created about 6 years ago
Updated over 5 years ago

AlaaAnani/Minesweepers-Shielded-Arduino

AlaaAnani

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This is the code used on the sheilded Arduino during the competition Minesweepers '18. The sketch uses UDP protocol for receiving and sending data to the control station (LabVIEW) like the received sensors data. It also receives commands from the station for certain tasks; Joystick control, reset signal, activating PID control for angle and PWM adjustment.

Hough-Rectangle-and-Circle-Detection

This Python project coded using Numpy implements line, rectangle and circle Hough Transform. It takes an image, determines the lines, rectangles and circles in it and also counts the money in the photo. [Calibrated on the provided test set only].

CNN-from-Scratch-Cupy

This is a fully vectorized CNN components repo: Dense, Conv2D, Max Pool and Flatten layers.

adaptive-certify

Implementation of adaptive hierarchical certification for segmentation using randomized smoothing.

Jupyter Notebook

UNet-Skeletonization

Skeletonization using UNet architecture from scratch in Python

LaserTagGame-Embedded

This project aims to implement a lasertag game system on the STML432KC nucleo-board. The game logic follows a usual lasertag game.

CUDA-SpMV-Using-ELL-Sectioned-JDS-Format

KarelSolver-PolicyGradientAlgorithms

This is a Karel task solver (4x4) that uses RL Policy Gradient Algorithms.

UNIX-Shell

This is a UNIX shell. Project 1 in the Programming Projects of Chapter 3 in Operating Systems Textbook.

ROV-ROS-ws

Distributed

Traffic-Signs-Object-Detection

This project coded in Python uses opencv functions and a CNN model to detect traffic signs containing at least red and yellow colors.

Minesweepers-Sesnors-Arduino

These are the codes used during the competition Minesweepers '18. The microcontroller used was Arduino Uno. Two Arduinos were used, one for sensors and the other was shielded with an Ethernet shield for wireless data communication.

Reinfrocement-Learning

This repo contains the solutions for the exercises of the Reinforcement Learning 2020 Textbook by Richard S. Sutton and Adrew G. Barto found here (https://www.amazon.de/Reinforcement-Learning-Introduction-Adaptive-Computation/dp/0262039249/ref=asc_df_0262039249/?tag=googshopde-21&linkCode=df0&hvadid=310780588948&hvpos=&hvnetw=g&hvrand=1059996085859779745&hvpone=&hvptwo=&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9060722&hvtargid=pla-458692329113&psc=1&th=1&psc=1&tag=&ref=&adgrpid=61876418335&hvpone=&hvptwo=&hvadid=310780588948&hvpos=&hvnetw=g&hvrand=1059996085859779745&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9060722&hvtargid=pla-458692329113).