BERT-based AI-generated academic text detection model
Privacy-first student submission platform with LaTeX support, auto-save, and AI documentation. Generate professional PDFs for Gradescope - all client-side.
A full-stack LMS for quiz management with secure authentication, plagiarism detection, and percentile-based evaluation.
A full-stack coding test platform with real-time code submission, plagiarism detection, and auto-evaluation using Judge0. Built with Next.js, Firebase Auth, and MongoDB. Designed to help educators ensure academic integrity.
AI-powered document originality and plagiarism risk detection system combining semantic similarity (SBERT), stylometric analysis, and citation masking for explainable, multi-layered originality scoring.
Aseel AI – Intelligent Academic Integrity Platform powered by AI and Computer Vision for analyzing and verifying university projects.
🛡️ AI-Powered Exam Proctoring System | YOLOv8 + ESP32 IoT | Multi-Camera Support
Smart academic dashboard for analyzing and verifying the originality of university projects using AI-powered insights.
C-PlagAST is a code plagiarism detection tool for C programs using the AST-CC algorithm. It normalizes and compares abstract syntax trees to detect structural similarity, even with reordered or renamed code. Ideal for academic use in detecting hidden code duplication.
repositorio que documenta las inconsistencias en el analisis de la base de datos presentada por el Programa de Poltica de Drogas del CIDE
A Twine game about three real people who didn't get the credit they deserved, and why that should matter to undergraduate college students.
Secure homework assignment and collection system with advanced copy protection, teacher management dashboard, and student code-based access. Built with Next.js, TypeScript, and PostgreSQL.
A reflective essay by Peter Kahl on the fight against institutional injustice, the silence of journalism, and why courageous researchers must persist—even without a smoking gun.
Check a directory of student submissions for similarities using a similarity hash.
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