Projects
Open source projects powered by @SEΛN
Developed a 3D medical image segmentation model for post-treatment brain tumors, applying state-space modeling techniques on the BraTS 2024 dataset.
X-Mamba
Developed a 3D medical image segmentation model for post-treatment brain tumors, applying state-space modeling techniques on the BraTS 2024 dataset.
A comprehensive data processing system built with Apache Flink for smart home automation and monitoring. The system integrates various sensors, face/voice recognition capabilities, and real-time data processing.
YOLOHome - Smart Home Data Processing System
A comprehensive data processing system built with Apache Flink for smart home automation and monitoring. The system integrates various sensors, face/voice recognition capabilities, and real-time data processing.
Technologies
About
YOLOHome is an advanced smart home data processing system that leverages Apache Flink for real-time stream processing. The system combines IoT sensor data with AI-powered face and voice recognition to create an intelligent home automation platform. It features real-time data ingestion from multiple sensor types, object detection using YOLO algorithms, and automated decision-making based on occupancy patterns.
A comprehensive web-based printing management system for university students with smart features and modern UI.
Student Smart Printing Service
A comprehensive web-based printing management system for university students with smart features and modern UI.
Technologies
About
The Student Smart Printing Service is a full-stack web application designed to streamline printing services in university environments. It features user authentication, print job management, quota tracking, payment integration, and administrative controls. Built with modern web technologies, it provides a seamless experience for both students and administrators.
RAG-with-LangChain
A simple project to demonstrate how to use LangChain with RAG.
Technologies
About
This project demonstrates the implementation of Retrieval-Augmented Generation (RAG) using LangChain framework. It showcases how to build intelligent question-answering systems that can retrieve relevant information from a knowledge base and generate contextually accurate responses using large language models.