Image classification technology has shown remarkable improvement over the past few years, exemplified in part by the?Imagenet?classification challenge, where error rates continue to?drop substantially every year.
In order to continue advancing the state of the art in computer vision, many researchers are now putting more focus on fine-grained and instance-level recognition problems ? instead of recognizing general entities such as buildings, mountains and (of course) cats, many are designing machine learning algorithms capable of identifying the Eiffel Tower, Mount Fuji or Persian cats. However, a significant obstacle for research in this area has been the lack of large annotated datasets.In this project we have implemented landmark recognition using? RCNN.