RS
R.M. Siebes
6 records found
1
Computer vision and architectural history at eye level
Mixed methods for linking research in the humanities and in information technology (ArchiMediaL)
Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valua
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AmsterTime
A Visual Place Recognition Benchmark Dataset for Severe Domain Shift
We introduce AmsterTime: a challenging dataset to benchmark visual place recognition (VPR) in presence of a severe domain shift. AmsterTime offers a collection of 2,500 well-curated images matching the same scene from a street view matched to historical archival image data from A
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Deep Learning from History
Unlocking Historical Visual Sources Through Artificial Intelligence
Historical photos of towns and villages contain a great deal of information about the built environment of the past. However, it is difficult to evaluate the information of images that are not labeled or incorrectly labeled or not organized in repositories or collections. In orde
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The ArchiMediaL project aims to bridge between data science and researches on contemporary and historical built environments by developing state of the art AI algorithms for the automatic linking of available meta-data and image repositories. As a case-study we use the 360,000+ h
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Built form dominates the urban space where most people live and work and provides a visual reflection of the local, regional and global esthetical, social, cultural, technological and economic factors and values. Street-view images and historical photo archives are therefore an i
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We address the interpretability of convolutional neural networks (CNNs) for predicting a geo-location from an image. In a pilot experiment we classify images of Pittsburgh vs Tokyo and visualize the learned CNN filters. We found that varying the CNN architecture leads to variatin
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