A Unified Vision–Language Approach for Predicting Geographic Locations  from Natural Images through Object, Scene, and Landmark Understanding

Dr. S Pratap Singh, Dr. Ch.Bindhu Madhuri, Dr. P Satheesh

A Unified Vision–Language Approach for Predicting Geographic Locations from Natural Images through Object, Scene, and Landmark Understanding

Authors

Dr. S Pratap Singh, Dr. Ch.Bindhu Madhuri, Dr. P Satheesh

Keywords:

Vision–language models, geolocation prediction, object detection, multimodal learning, scene understanding, CLIP, YOLOv11, geographic intelligence.

Abstract

The task of predicting geographic locations from natural images remains a significant challengedue to complex visual variability and the lack of explicit spatial cues. This paper presents a unified vision–language

References

J. Hays and A. A. Efros, “IM2GPS: Estimating geographic information from a single image,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–8, 2008.

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Published

2024-12-20

How to Cite

Dr. S Pratap Singh, Dr. Ch.Bindhu Madhuri, Dr. P Satheesh. (2024). A Unified Vision–Language Approach for Predicting Geographic Locations from Natural Images through Object, Scene, and Landmark Understanding. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 7079–7087. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4116