TY  - CONF
AU  - Adria Molina
AU  - Lluis Gomez
AU  - Oriol Ramos Terrades
AU  - Josep Llados
A2  - DAS
PY  - 2022//
TI  - A Generic Image Retrieval Method for Date Estimation of Historical Document Collections
BT  - Document Analysis Systems.15th IAPR International Workshop, (DAS2022)
SP  - 583–597
VL  - 13237
KW  - Date estimation
KW  - Document retrieval
KW  - Image retrieval
KW  - Ranking loss
KW  - Smooth-nDCG
N2  - Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images.
L1  - http://refbase.cvc.uab.es/files/MGR2022.pdf
UR  - http://dx.doi.org/10.1007/978-3-031-06555-2_39
N1  - DAG; 600.140; 600.121
ID  - Adria Molina2022
ER  -