Fake Image Detection using Hugging Face and Blockchain Framework

G. Durga Prasanna1, E. Harshith2, K. Harika3, S. Geetha Naga Swarupa4, K. Sai Prakash5,
Dr Satyanarayana Tirlangi6
1,2,3,4,5,6Department of Computer Science and Engineering & Visakha Institute of Engineering & Technology(A)

Abstract - The rapid advancement of technology and the increasing availability of educational data have created new opportunities to apply machine learning techniques in academic performance prediction. This project, titled “FAKE IMAGE DETECTION USING HUGGING FACE AND BLOCKCHAIN FRAMEWORK,” aims to develop an intelligent system that predicts students’ academic performance by analyzing multiple influencing factors beyond traditional academic scores. The proposed system considers various academic, socioeconomic, and environmental parameters such as previous academic performance, attendance, study hours, internet availability,family income, health conditions, and environmental disruptions. By processing these inputs using machine learning algorithms, the system predicts the nextsemester SGPA and determines whether a student is academically at risk or not. The system is implemented as a web-based applicationusing technologies such as Python, Streamlit, and machine learning models. It provides a user-friendly interface for students and administrators to enter data, view predictions, and generate performance reports. This system helps educational institutions identify students who require early academic support, improve academic performance, and enable data-driven decision-making in the education sector.Keywords: Machine Learning, Academic Prediction, Student Performance, Risk Detection, Educational Data Mining, Socio-Economic
Factors, Predictive Analytics