SililaWijesinghe
Android Developer | Web Application Developer | Standalone Applications Developer | Computer Vision
Kurunegala, Sri Lanka
Pinned Repositories
HD222KU-DEMO
EmployeeManagementApplication
Android + Java + Firebase
Food-Ordering-System-HTML-CSS-JAVASCRIPT-PHP-MYSQL-PHPMYADMIN-Website-with-the-ADMIN-PANEL
This repository contains a streamlined Food Ordering System with an admin panel, built using HTML, CSS, JavaScript, PHP, and MySQL via PHPMyAdmin. It offers an intuitive interface for users to easily order food. Ideal for a quick setup of an online food ordering platform with efficient data management.
My-Resume
NIBM-Student-CRUD-Android-App-Java-Firebase-Android-Studio-Recycler-View-2024
An Java Android app for managing student information using Firebase.
ShoppingListApplication
Crafted with C# in Visual Studio, this Windows Forms Application serves as an efficient Shopping List tool. The application leverages the power of a Linked List data structure, offering dynamic and flexible list management. Users can easily add, remove, and modify items on their shopping list, providing a seamless and intuitive experience.
Singer-Stock-Management-Web-Application-HTML-CSS-JAVASCRIPT-PHP-BOOTSTRAP-PHPMyADMIN
A stock management web application for Singer Company built using HTML, CSS, JAVASCRIPT, PHP
Student-Portal-CRUD-Android-App-Java-Firebase-AndroidStudio
This Android application, developed using Java and Firebase, serves as a comprehensive Student Portal with CRUD (Create, Read, Update, Delete) functionality. Built within Android Studio, the app provides a seamless user experience for students to manage their academic information efficiently.
Vegetable-Detection-with-Tensorflow-learning-PYTHON
One notebook trains a vegetable classification model with InceptionV3 using TensorFlow and Keras. The second notebook showcases the pre-trained model's inference on vegetable categories, loading InceptionV3 and enhancing image features. Together, they offer a compact solution for vegetable classification through deep learning.
SililaWijesinghe's Repositories
SililaWijesinghe/Food-Ordering-System-HTML-CSS-JAVASCRIPT-PHP-MYSQL-PHPMYADMIN-Website-with-the-ADMIN-PANEL
This repository contains a streamlined Food Ordering System with an admin panel, built using HTML, CSS, JavaScript, PHP, and MySQL via PHPMyAdmin. It offers an intuitive interface for users to easily order food. Ideal for a quick setup of an online food ordering platform with efficient data management.
SililaWijesinghe/NIBM-Student-CRUD-Android-App-Java-Firebase-Android-Studio-Recycler-View-2024
An Java Android app for managing student information using Firebase.
SililaWijesinghe/EmployeeManagementApplication
Android + Java + Firebase
SililaWijesinghe/My-Resume
SililaWijesinghe/ShoppingListApplication
Crafted with C# in Visual Studio, this Windows Forms Application serves as an efficient Shopping List tool. The application leverages the power of a Linked List data structure, offering dynamic and flexible list management. Users can easily add, remove, and modify items on their shopping list, providing a seamless and intuitive experience.
SililaWijesinghe/Singer-Stock-Management-Web-Application-HTML-CSS-JAVASCRIPT-PHP-BOOTSTRAP-PHPMyADMIN
A stock management web application for Singer Company built using HTML, CSS, JAVASCRIPT, PHP
SililaWijesinghe/Student-Portal-CRUD-Android-App-Java-Firebase-AndroidStudio
This Android application, developed using Java and Firebase, serves as a comprehensive Student Portal with CRUD (Create, Read, Update, Delete) functionality. Built within Android Studio, the app provides a seamless user experience for students to manage their academic information efficiently.
SililaWijesinghe/Vegetable-Detection-with-Tensorflow-learning-PYTHON
One notebook trains a vegetable classification model with InceptionV3 using TensorFlow and Keras. The second notebook showcases the pre-trained model's inference on vegetable categories, loading InceptionV3 and enhancing image features. Together, they offer a compact solution for vegetable classification through deep learning.