%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/14572644/4 %R 10.4121/14572644.v4 %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