
According to the world health organization, Cancer is the second leading cause of death globally. An accurate Breast Cancer diagnosis ensures that the patient is given the correct and the most effective treatment plan and procedures. Manual Histopathology exams done by pathologists are complex, time consuming, and prone to misinterpretations due to the difference in pathologists expertise. So, the main idea of our proposed system is to diagnose breast cancer types from microscopy Biopsy images using Deep Learning algorithms.

Immediate and informative feedback are crucial yet difficult to achieve with manual assignment marking. EvalSeer is a gamified LMS equipped with code auto-marking. It offers instant feedback, leaderboard, badges, and score-based tasks (Code and peer-review) in a competitive environment. EvalSeer shall present continuous challenges to keep students motivated while utilising automated assessment to produce current visual insights on students’ progress. Deep Learning will be used to suggest syntax error fixes to the code.

Our project will focus on recognizing monuments from a video , the monument recognized can be either in a clear view or hidden by any sort of objects.We will be using a traditional and non-traditional machine learning and deep learning techniques to recognize these monuments and then we will add an augmented reality layer that will act as a guide.This project will target tourists as it will make their experience in heritage sites better.
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