Projects
Our face recognition-based attendance tracking system has a lot of promise in a variety of environments, including companies, events, colleges, and schools. It could increase effectiveness and precision.
The aim of this project is to create a facial recognition-based attendance system. To record attendance, the system will take a picture of a student's or employee's face and compare it to a database of faces that have been registered. By doing away with manual attendance taking, the system will save time and minimize errors.
Plagiarism is a common issue in academia and the digital age has made it easier for individuals to copy and paste content from various sources without proper attribution. To address this problem, we propose a plagiarism checker that uses natural language processing (NLP) techniques to identify similarities between documents. Our system analyzes text at a semantic level, looking for patterns of language use and word choice to determine if there are any matches between the source and target documents.
​In today's environment, fake news is a growing worry because it may have detrimental effects on both people and society as a whole. Misinformation can harm people by swaying public opinion, twisting the truth, and encouraging false beliefs. Therefore, it has become crucial to create techniques to identify bogus news.Machine learning models have showed potential in identifying bogus news in recent years. The Long Short-Term Memory (LSTM) network, a kind of recurrent neural network that can handle data sequences, is one such model.
© Vemula Kasinath