Zobrazeno 1 - 10
of 251
pro vyhledávání: '"Oriol Ramos"'
The use of image analysis in automated photography management is an increasing trend in heritage institutions. Such tools alleviate the human cost associated with the manual and expensive annotation of new data sources while facilitating fast access
Externí odkaz:
http://arxiv.org/abs/2409.03911
This paper introduces Fetch-A-Set (FAS), a comprehensive benchmark tailored for legislative historical document analysis systems, addressing the challenges of large-scale document retrieval in historical contexts. The benchmark comprises a vast repos
Externí odkaz:
http://arxiv.org/abs/2406.07315
Autor:
Boned, Carlos, Talarmain, Maxime, Ghanmi, Nabil, Chiron, Guillaume, Biswas, Sanket, Awal, Ahmad Montaser, Terrades, Oriol Ramos
This paper presents a new synthetic dataset of ID and travel documents, called SIDTD. The SIDTD dataset is created to help training and evaluating forged ID documents detection systems. Such a dataset has become a necessity as ID documents contain pe
Externí odkaz:
http://arxiv.org/abs/2401.01858
Autor:
Bakkali, Souhail, Biswas, Sanket, Ming, Zuheng, Coustaty, Mickaël, Rusiñol, Marçal, Terrades, Oriol Ramos, Lladós, Josep
Visual document understanding (VDU) has rapidly advanced with the development of powerful multi-modal language models. However, these models typically require extensive document pre-training data to learn intermediate representations and often suffer
Externí odkaz:
http://arxiv.org/abs/2309.05756
Autor:
Aura Hernàndez-Sabaté, Lluís Albarracín, Oriol Ramos, Debora Gil, Carles Sánchez, Enric Martí
Publikováno v:
Journal of Technology and Science Education, Vol 14, Iss 3, Pp 798-814 (2024)
Computer engineering students should develop competences related to the contents of databases design and SQL queries. For this purpose, the recommendations on the convenience of changing the traditional teaching methodology to the flipped classroom a
Externí odkaz:
https://doaj.org/article/eba7859844ad40b9bbac7f1b24c01307
Multimodal learning from document data has achieved great success lately as it allows to pre-train semantically meaningful features as a prior into a learnable downstream task. In this paper, we approach the document classification problem by learnin
Externí odkaz:
http://arxiv.org/abs/2205.12029
Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others.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 ret
Externí odkaz:
http://arxiv.org/abs/2204.04028
Autor:
Centeno, Albert Berenguel, Terrades, Oriol Ramos, Canet, Josep Lladós, Morales, Cristina Cañero
Counterfeiting and piracy are a form of theft that has been steadily growing in recent years. Banknotes and identity documents are two common objects of counterfeiting. Aiming to detect these counterfeits, the present survey covers a wide range of an
Externí odkaz:
http://arxiv.org/abs/1910.08993
Publikováno v:
In Pattern Recognition July 2023 139
Autor:
Cruz, Francisco, Terrades, Oriol Ramos
We successfully combine Expectation-Maximization algorithm and variational approaches for parameter learning and computing inference on Markov random felds. This is a general method that can be applied to many computer vision tasks. In this paper, we
Externí odkaz:
http://arxiv.org/abs/1805.02536