  This paper presents a visual geo-localization system capable of determining
the geographic locations of places (buildings and road intersections) from
images without relying on GPS data. Our approach integrates three primary
methods: Scale-Invariant Feature Transform (SIFT) for place recognition,
traditional image processing for identifying road junction types, and deep
learning using the VGG16 model for classifying road junctions. The most
effective techniques have been integrated into an offline mobile application,
enhancing accessibility for users requiring reliable location information in
GPS-denied environments.
