%0 Generic
%A Yildiz, Burak
%A Khademi, Seyran
%D 2022
%T Extracted Features on AmsterTime Dataset
%U https://data.4tu.nl/articles/dataset/Extracted_Features_of_Amsterdam_Cross-time_Dataset/14572644/3
%R 10.4121/14572644.v3
%K features
%K Amsterdam
%K Cross-time
%K deep learning
%K SIFT features
%K LIFT features
%K ResNet features
%K NetVLAD features
%K VGGNet features
%K AmsterTime
%X <p>This collection contains feature files where the features are extracted on AmsterTime dataset using various methods and models such as SIFT, LIFT, and pre-trained VGG-16, ResNets, NetVLAD, AP-GeM and supervisely and self-supervisely trained models. The details of feature extraction procedure and other details can be found on https://github.com/seyrankhademi/AmsterTime.<br>
</p>
%I 4TU.ResearchData