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English(EN) GeoSEAN: Explainable Country-Level Image Geolocation for ASEAN Regions

GeoSEAN模型为东南亚地区提供可解释的国家级图像地理定位

研究人员开发了GeoSEAN,一个针对东南亚地区国家级图像地理定位的新颖系统,解决了跨国界相似视觉特征的挑战。该系统利用多层感知器(MLP)分类器,在4,850张图像的数据集上实现了85.91%的准确率和F1分数。GeoSEAN通过采用CLIP注意力展开、YOLOv2对象检测和基于能量的指向游戏指标来分析其预测背后的视觉线索,增强了可解释性,揭示了对象频率并不总是与注意力密度相关。 AI

影响 这项研究推进了地理定位任务中计算机视觉领域的可解释人工智能技术。

排序理由 该集群包含一篇详细介绍新模型和方法的学术论文。

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GeoSEAN模型为东南亚地区提供可解释的国家级图像地理定位

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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Muhamad Syukron, Danish Rafie Ekaputra, Tintrim Dwi Ary Widhianingsih ·

    GeoSEAN: 东南亚地区可解释的国家级图像地理定位

    arXiv:2607.12284v1 Announce Type: new Abstract: Image geolocation aims to infer the geographic origin of an image from visual content alone. However, this task remains challenging in regions where countries share similar urban, roadside, architectural, and environmental character…

  2. arXiv cs.CV TIER_1 English(EN) · Tintrim Dwi Ary Widhianingsih ·

    GeoSEAN: 东南亚地区可解释的国家级图像地理定位

    Image geolocation aims to infer the geographic origin of an image from visual content alone. However, this task remains challenging in regions where countries share similar urban, roadside, architectural, and environmental characteristics. Many existing geolocation models focus o…