Handwritten Document Analysis for Automatic Writer Recognition

Autor: Ameur Bensefia, Thierry Paquet, Laurent Heutte

Publikováno v: ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 5, Iss 2 (2005)

In this paper, we show that both the writer identification and the writer verification tasks can be carried out using local features such as graphemes extracted from the segmentation of cursive handwriting. We thus enlarge the scope of the possible u

Externí odkaz: https://doaj.org/article/27f0057076f240bca51a9d726f5fbd6d

Image Retrieval and Pattern Spotting on Historical Documents with Binary Descriptors

Autor: Zacarias Curi, Stephane Nicolas, Pierrick Tranouez, Alceu de S. Britto, Laurent Heutte

Publikováno v: 2022 26th International Conference on Pattern Recognition (ICPR).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b53c8893a6ec21f9a4407435dd9cf098
https://doi.org/10.1109/icpr56361.2022.9956416

Improving pattern spotting in historical documents using feature pyramid networks

Autor: Ignacio Úbeda, Laurent Heutte, Jose M. Saavedra, Caroline Petitjean, Stéphane Nicolas

Publikováno v: Pattern Recognition Letters. 131:398-404

Pattern spotting consists of locating different instances of a given object (i.e. an image query) in a collection of historical document images. These patterns may vary in shape, size, color, context and even style because they are hand-drawn, which

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::72ceecf822e70c2c8e0049f9f93a94fb
https://doi.org/10.1016/j.patrec.2020.02.002

A Novel Random Forest Dissimilarity Measure for Multi-View Learning

Autor: Hongliu Cao, Simon Bernard, Laurent Heutte, Robert Sabourin

Publikováno v: ICPR

Multi-view learning is a learning task in which data is described by several concurrent representations. Its main challenge is most often to exploit the complementarities between these representations to help solve a classification/regression task. T

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::349de7fe554b3c82617c7f537fb296d9
http://arxiv.org/abs/2007.02572

Pattern spotting in historical documents using convolutional models

Autor: Laurent Heutte, Ignacio Úbeda, Jose M. Saavedra, Stéphane Nicolas, Caroline Petitjean

Publikováno v: 5th International Workshop on Historical Document Imaging and Processing, HIP 2019, Sydney, Australia, Sept 2019
5th International Workshop on Historical Document Imaging and Processing, HIP 2019, Sydney, Australia, Sept 2019, ICDAR2019, Sep 2019, Sydney, Australia. pp.60-65, ⟨10.1145/3352631⟩
HIP@ICDAR

Pattern spotting consists of searching in a collection of historical document images for occurrences of a graphical object using an image query. Contrary to object detection, no prior information nor predefined class is given about the query so train

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39d89dbf83ea1fb6287c42d130d2507c
https://hal.archives-ouvertes.fr/hal-02335779