Pinned Repositories
7Segment_Driver
AVR 7-Segment Display Driver: Simplify control of 7-segment displays on Atmel AVR microcontrollers. Easily manage digits, segments, and multiplexing for numeric and character display applications. Streamline your projects with an efficient and flexible solution with a counter application.
7Segment_Watch
Explore the synergy of hardware and software with our 7-Segment Driver project,The accompanying Watch Application demonstrates practical usage, while the Proteus Simulation offers an interactive environment to experiment with the technology. Join us in unraveling the world of digital displays, microcontroller programming, and simulation.
Auto-Parallel-Parking-Car
Parallel Parking Car , an open-source initiative that leverages Arduino Uno for building a smart and efficient parking assistance system. This project is designed to enhance your understanding of robotics, Arduino programming, and parallel parking algorithms.
CartPole-Reinforcement-Learning-Algorithms
This project implements three different reinforcement learning algorithms—Monte Carlo, Q-learning, and SARSA—on the classic CartPole problem.
char-generation-word-generation-RNN-models-
applying different RNN architecture to build character prediction model and a word based prediction model these model are trained on data of specific topics from wikipedia
cost-function-MSE-
cost function implementation
DIO_Driver
AVR DIO Driver: Simplify digital pin management on Atmel AVR microcontrollers. Streamline interfacing with external components using this efficient library for digital input/output operations. Easily configure pins, toggle states, and implement GPIO functionality in your AVR projects.
Hamming-Network
Hamming Network implementation using pca implementation for reduction all from scratch
PYKE-expert-system
an Expert System in Egyption divorce law
sun-tracing-solarPanel
Sun Tracking Solar Panel: An embedded systems marvel! Harness the power of ATmega32, 2 LDRs, and a servo motor to automatically optimize solar panel orientation for maximum energy efficiency. A microcontroller-driven solution for sustainable energy generation
Samahussien7's Repositories
Samahussien7/DIO_Driver
AVR DIO Driver: Simplify digital pin management on Atmel AVR microcontrollers. Streamline interfacing with external components using this efficient library for digital input/output operations. Easily configure pins, toggle states, and implement GPIO functionality in your AVR projects.
Samahussien7/7Segment_Watch
Explore the synergy of hardware and software with our 7-Segment Driver project,The accompanying Watch Application demonstrates practical usage, while the Proteus Simulation offers an interactive environment to experiment with the technology. Join us in unraveling the world of digital displays, microcontroller programming, and simulation.
Samahussien7/Auto-Parallel-Parking-Car
Parallel Parking Car , an open-source initiative that leverages Arduino Uno for building a smart and efficient parking assistance system. This project is designed to enhance your understanding of robotics, Arduino programming, and parallel parking algorithms.
Samahussien7/Hamming-Network
Hamming Network implementation using pca implementation for reduction all from scratch
Samahussien7/PYKE-expert-system
an Expert System in Egyption divorce law
Samahussien7/sun-tracing-solarPanel
Sun Tracking Solar Panel: An embedded systems marvel! Harness the power of ATmega32, 2 LDRs, and a servo motor to automatically optimize solar panel orientation for maximum energy efficiency. A microcontroller-driven solution for sustainable energy generation
Samahussien7/7Segment_Driver
AVR 7-Segment Display Driver: Simplify control of 7-segment displays on Atmel AVR microcontrollers. Easily manage digits, segments, and multiplexing for numeric and character display applications. Streamline your projects with an efficient and flexible solution with a counter application.
Samahussien7/CartPole-Reinforcement-Learning-Algorithms
This project implements three different reinforcement learning algorithms—Monte Carlo, Q-learning, and SARSA—on the classic CartPole problem.
Samahussien7/char-generation-word-generation-RNN-models-
applying different RNN architecture to build character prediction model and a word based prediction model these model are trained on data of specific topics from wikipedia
Samahussien7/cost-function-MSE-
cost function implementation
Samahussien7/fastText-Model
fast text model on yelp dataset and used pretrained on to compare results
Samahussien7/Game-rital-database
database system include (ERD, Physical model and set of select statements) ➢ Software Application using C# programming language
Samahussien7/Handwritten-Digit-Classification-Using-K-Means-Clustering
Using K-Means clustering, with feature extraction comparison between centroid and chaincode methods.. The script implements K-Means clustering from scratch, performs feature extraction using both centroid and chaincode techniques, evaluates classification accuracy, and compares the effectiveness of the two feature extraction methods.
Samahussien7/linear-regression
linear regression implementation with gradient decent
Samahussien7/Parking-System
software parking system which works on 2 algorithms first come first served , best fit and calculate fees
Samahussien7/Waiter_Robot
Waiter robot software design working autonomously using A* algorithm to deliver tables consuming the less possible energy and time
Samahussien7/COVID-19-Chest-X-ray-Classification-KNN
This project aims to build a complete pattern recognition system to solve classification problems using the k-Nearest Neighbors (KNN) algorithm. To classify chest X-ray images into three categories: COVID-19 positive, pneumonia positive, and normal. To achieve this, we utilize the COVID-19 Chest X-ray dataset available on Kaggle.
Samahussien7/Handwritten-Digit-Recognition-Centroids
This Python script demonstrates the process of training a classifier to recognize handwritten digits using the MNIST dataset. The script utilizes centroid-based feature extraction, splits the data into training and testing sets, employs a classifier, and evaluates its accuracy.
Samahussien7/Handwritten-Digit-Recognition-with-Chaincode-Feature-Extraction
This script recognize handwritten digits using the MNIST dataset. Implementation using chaincode-based feature extraction, which offers an alternative method for capturing relevant information from digit images. The script divides the data into training and testing sets, utilizes a classifier, and evaluates its accuracy.
Samahussien7/HTML-Text-Processing-and-Unique-Word-Extraction
This Python script extracts text content from an HTML page, processes it, and extracts unique words from the processed text. The script utilizes various text processing techniques including cleaning, normalization, tokenization, lemmatization or stemming, and stop words removal.
Samahussien7/Image-Arithmetic-Operations
This Python script performs various arithmetic operations on an input image, including addition, subtraction, multiplication, and inversion. These operations allow for manipulation of pixel values in the image, resulting in different visual effects.
Samahussien7/Image-Histogram-Analysis-and-Enhancement
This Python script analyzes image histograms and performs various histogram-based enhancements, including histogram shift, histogram equalization, and contrast stretching. These techniques aim to improve the visual quality and enhance the contrast of digital images.
Samahussien7/TF-IDF-from-Scratch-with-Text-Generation
This project aims to implement the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm from scratch in two different ways, accompanied by text generation methods. TF-IDF is a widely used technique in natural language processing and information retrieval to represent the importance of a term within a document relative to a collection of doc
Samahussien7/Twitter-Sentiment-Analysis-using-CNN
This project aims to perform sentiment analysis on a Twitter dataset using Convolutional Neural Networks (CNNs). The goal is to classify tweets into positive, negative, or neutral sentiments.
Samahussien7/Video-Subtitles-Detector
The Video Subtitles Detector is designed to detect and highlight subtitles within a video. It identifies the area containing the subtitles by drawing bounding boxes around them and further detects the location of each word within the subtitles. The program processes the video using basic filters and morphological operations.