Mohamed Abd El-Monem's Projects
Text Classfication Project on an Arabic News Dataset "Akhbarona" from Text Classfication Project on an Arabic News Dataset "Akhbarona" from Single-Label Arabic News Articles Dataset for Automatic Text Categorization (SANAD) - https://data.mendeley.com/datasets/57zpx667y9/2
Like Shazam, Audio Fingerprinting Application with Python and Qt Designer (PyQt5).
Mobile Application designed for children. It makes learning English more exciting and delightful through developing the main four skills of learning; listening, reading, speaking and writing.
Mobile Application designed for children. It makes learning English more exciting and delightful through developing the main four skills of learning; listening, reading, speaking and writing.
Desktop Application using Python and Qt, The App is responsible for doing Pairwise Multiple Sequences Alignment (Global & Local), Multiple Sequence Alignment, Generating Phylogenetic tree, Calculating Percentage of Chemical Components in DNA (A, C, G, T) & RNA (A, C, G, U), Converting DNA to RNA (Transcription), and Converting DNA to Protein (Translation).
Mobile app integrated with Google Books API that can perform full-text searches and retrieve book information, viewability and eBook availability. You can also manage your personal bookshelves.
Building a detection model using a Convolutional Neural Network in Tensorflow & Keras. Used a brain MRI images dataset founded on Kaggle.
Analysis for the Heart Disease Dataset, by doing some features correlations, going through some quick plot visualizations, analyzing them and getting some conclusions. And then will proceed to apply several ML models to see which yields better results and finishing with Classifier models
Financial Sentiment Analysis on Kaggle Dataset using differnet NLP techniques such as RNN, LSTM, and GRU - https://www.kaggle.com/datasets/sbhatti/financial-sentiment-analysis
Create output images corresponding to different texture descriptors. We will then use these descriptors to enhance the Region Growing segmentation algorithm.
It's a Demo Desktop Application which is responsible for performing Image Processing techniques such as: Adding, Removing Noise, Detecting Edges, Filtering, Histogram, Equalizing Images.
The goal of this tutorial is to investigate the usefulness of two clustering-based methods namely, Fuzzy C-mean (FCM) and Expectation-Maximization (EM) algorithms
The goal of this tutorial is to investigate the effectiveness of the region growing (RG) algorithm for image segmentation. We'll apply the RG algorithm to 2D and 3D images.
Convert the RAW mammographic image to be similar to the PRESENTATION one using Python Script
Building different regression models on Concrete Data to get best Concrete Compressive Strength
Sentiment Analysis for sample text by using NLTK library
Trying YOLO Algorithm on Images, and Videos.