Automatic location detection based on deep learning
Anjali Karangiya Anirudh Sharma Divax Shah Kartavya Badgujar Dr. Chintan Thacker Dainik Dave
The proliferation of digital images and the advancements in deep learning
have paved the way for innovative solutions in various domains, especially in
the field of image classification. Our project presents an in-depth study and
implementation of an image classification system specifically tailored to
identify and classify images of Indian cities. Drawing from an extensive
dataset, our model classifies images into five major Indian cities: Ahmedabad,
Delhi, Kerala, Kolkata, and Mumbai to recognize the distinct features and
characteristics of each city/state. To achieve high precision and recall rates,
we adopted two approaches. The first, a vanilla Convolutional Neural Network
(CNN) and then we explored the power of transfer learning by leveraging the
VGG16 model. The vanilla CNN achieved commendable accuracy and the VGG16 model
achieved a test accuracy of 63.6%. Evaluations highlighted the strengths and
potential areas of improvement, positioning our model as not only competitive
but also scalable for broader applications. With an emphasis on open-source
ethos, our work aims to contribute to the community, encouraging further
development and diverse applications. Our findings demonstrate the potential
applications in tourism, urban planning, and even real-time location
identification systems, among others.