Hello.

I trained a machine learning model to differentiate between buttons and links on web pages. Using a dataset of ~3000 button images and ~4000 link images, I trained a convolutional neural network (CNN) with added noise for better generalization. Preprocessing included grayscale conversion, dataset diversification with multilingual sites, and image compression. The model performed well in initial tests, correctly classifying button-like and link-like elements. Next, I'll build a web app for easier testing and a Lighthouse audit for website analysis.

I've shared my Call Detail Record (CDR) Generator, a Microsoft Access 2003 application I developed for my final year project. This tool creates thousands of simulated phone calls, mimicking various customer profiles (e.g., high/low usage, fraudulent, national rate). It offers extensive customization options for call cost, duration, and user behavior patterns (e.g. business vs. home user calling time). The generated call data is designed for training neural networks. Feel free to download and experiment – it's easy to use.