Researchers have developed GeoSEAN, a novel system for country-level image geolocation within ASEAN regions, addressing the challenge of similar visual characteristics across borders. The system utilizes a multilayer perceptron (MLP) classifier, achieving an 85.91% accuracy and F1 score on a dataset of 4,850 images. GeoSEAN enhances explainability by employing CLIP attention rollout, YOLOv2 object detection, and Energy Based Pointing Game metrics to analyze the visual cues behind its predictions, revealing that object frequency does not always correlate with attention density. AI
IMPACT This research advances explainable AI techniques in computer vision for geographic localization tasks.
RANK_REASON The cluster contains an academic paper detailing a new model and methodology.
- Energy Based Pointing Game
- GeoGuessr
- GeoSEAN
- Google Images
- LightGBM
- Muhamad Syukron
- multilayer perceptron
- YOLOv2
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