| Records |
| Author |
Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
| Title |
Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method |
Type |
Conference Article |
| Year |
2011 |
Publication  |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
63-67 |
| Keywords |
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| Abstract |
In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG;ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RAT2011 |
Serial |
1788 |
| Permanent link to this record |
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| Author |
Volkmar Frinken; Andreas Fischer; Horst Bunke; Alicia Fornes |
| Title |
Co-training for Handwritten Word Recognition |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
314-318 |
| Keywords |
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| Abstract |
To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on large sets of labeled data. Traditionally, the training data has to be labeled manually, which is a laborious and costly process. Semi-supervised learning techniques offer methods to utilize unlabeled data, which can be obtained cheaply in large amounts in order, to reduce the need for labeled data. In this paper, we propose the use of Co-Training for improving the recognition accuracy of two weakly trained handwriting recognition systems. The first one is based on Recurrent Neural Networks while the second one is based on Hidden Markov Models. On the IAM off-line handwriting database we demonstrate a significant increase of the recognition accuracy can be achieved with Co-Training for single word recognition. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FFB2011 |
Serial |
1789 |
| Permanent link to this record |
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| Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard |
| Title |
Subgraph Spotting Through Explicit Graph Embedding: An Application to Content Spotting in Graphic Document Images |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
870-874 |
| Keywords |
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| Abstract |
We present a method for spotting a subgraph in a graph repository. Subgraph spotting is a very interesting research problem for various application domains where the use of a relational data structure is mandatory. Our proposed method accomplishes subgraph spotting through graph embedding. We achieve automatic indexation of a graph repository during off-line learning phase, where we (i) break the graphs into 2-node sub graphs (a.k.a. cliques of order 2), which are primitive building-blocks of a graph, (ii) embed the 2-node sub graphs into feature vectors by employing our recently proposed explicit graph embedding technique, (iii) cluster the feature vectors in classes by employing a classic agglomerative clustering technique, (iv) build an index for the graph repository and (v) learn a Bayesian network classifier. The subgraph spotting is achieved during the on-line querying phase, where we (i) break the query graph into 2-node sub graphs, (ii) embed them into feature vectors, (iii) employ the Bayesian network classifier for classifying the query 2-node sub graphs and (iv) retrieve the respective graphs by looking-up in the index of the graph repository. The graphs containing all query 2-node sub graphs form the set of result graphs for the query. Finally, we employ the adjacency matrix of each result graph along with a score function, for spotting the query graph in it. The proposed subgraph spotting method is equally applicable to a wide range of domains, offering ease of query by example (QBE) and granularity of focused retrieval. Experimental results are presented for graphs generated from two repositories of electronic and architectural document images. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1520-5363 |
ISBN |
978-1-4577-1350-7 |
Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ LRL2011 |
Serial |
1790 |
| Permanent link to this record |
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| Author |
Anjan Dutta; Josep Llados; Umapada Pal |
| Title |
Symbol Spotting in Line Drawings Through Graph Paths Hashing |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
982-986 |
| Keywords |
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| Abstract |
In this paper we propose a symbol spotting technique through hashing the shape descriptors of graph paths (Hamiltonian paths). Complex graphical structures in line drawings can be efficiently represented by graphs, which ease the accurate localization of the model symbol. Graph paths are the factorized substructures of graphs which enable robust recognition even in the presence of noise and distortion. In our framework, the entire database of the graphical documents is indexed in hash tables by the locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. The spotting method is formulated by a spatial voting scheme to the list of locations of the paths that are decided during the hash table lookup process. We perform detailed experiments with various dataset of line drawings and the results demonstrate the effectiveness and efficiency of the technique. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1520-5363 |
ISBN |
978-1-4577-1350-7 |
Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ DLP2011b |
Serial |
1791 |
| Permanent link to this record |
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| Author |
Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny |
| Title |
Wall Patch-Based Segmentation in Architectural Floorplans |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1270-1274 |
| Keywords |
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| Abstract |
Segmentation of architectural floor plans is a challenging task, mainly because of the large variability in the notation between different plans. In general, traditional techniques, usually based on analyzing and grouping structural primitives obtained by vectorization, are only able to handle a reduced range of similar notations. In this paper we propose an alternative patch-based segmentation approach working at pixel level, without need of vectorization. The image is divided into a set of patches and a set of features is extracted for every patch. Then, each patch is assigned to a visual word of a previously learned vocabulary and given a probability of belonging to each class of objects. Finally, a post-process assigns the final label for every pixel. This approach has been applied to the detection of walls on two datasets of architectural floor plans with different notations, achieving high accuracy rates. |
| Address |
Beiging, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1520-5363 |
ISBN |
978-0-7695-4520-2 |
Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ HMS2011a |
Serial |
1792 |
| Permanent link to this record |
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| Author |
Dimosthenis Karatzas; Sergi Robles; Joan Mas; Farshad Nourbakhsh; Partha Pratim Roy |
| Title |
ICDAR 2011 Robust Reading Competition – Challege 1: Reading Text in Born-Digital Images (Web and Email) |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1485-1490 |
| Keywords |
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| Abstract |
This paper presents the results of the first Challenge of ICDAR 2011 Robust Reading Competition. Challenge 1 is focused on the extraction of text from born-digital images, specifically from images found in Web pages and emails. The challenge was organized in terms of three tasks that look at different stages of the process: text localization, text segmentation and word recognition. In this paper we present the results of the challenge for all three tasks, and make an open call for continuous participation outside the context of ICDAR 2011. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1520-5363 |
ISBN |
978-1-4577-1350-7 |
Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ KRM2011 |
Serial |
1793 |
| Permanent link to this record |
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| Author |
Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados |
| Title |
The ICDAR 2011 Music Scores Competition: Staff Removal and Writer Identification |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1511-1515 |
| Keywords |
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| Abstract |
In the last years, there has been a growing interest in the analysis of handwritten music scores. In this sense, our goal has been to foster the interest in the analysis of handwritten music scores by the proposal of two different competitions: Staff removal and Writer Identification. Both competitions have been tested on the CVC-MUSCIMA database: a ground-truth of handwritten music score images. This paper describes the competition details, including the dataset and ground-truth, the evaluation metrics, and a short description of the participants, their methods, and the obtained results. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-0-7695-4520-2 |
Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FDG2011b |
Serial |
1794 |
| Permanent link to this record |
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| Author |
David Guillamet; Jordi Vitria |
| Title |
Discriminant Basis for Object Classification. |
Type |
Miscellaneous |
| Year |
2001 |
Publication |
11th International Conference on Image Analysis and Processing, ICIAP 2001, 256–261 |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Italia |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ GuV2001c |
Serial |
103 |
| Permanent link to this record |
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| Author |
A. Pujol; H. Wechsler; Juan J. Villanueva |
| Title |
Learning and Caricaturing the Face Space Using Self-Organization and Hebbian Learning for Face Processing. |
Type |
Miscellaneous |
| Year |
2001 |
Publication |
11th International Conference on Image Analysis and Processing, ICIAP 2001, 273–278. |
Abbreviated Journal |
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Issue |
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Pages |
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| Address |
Italia. |
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Series Title |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
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Approved |
no |
| Call Number |
ISE @ ise @ PWV2001 |
Serial |
205 |
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| Author |
Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades |
| Title |
Exploring the impact of inter-query variability on the performance of retrieval systems |
Type |
Conference Article |
| Year |
2014 |
Publication |
11th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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| Volume |
8814 |
Issue |
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Pages |
413–420 |
| Keywords |
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| Abstract |
This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. |
| Address |
Algarve; Portugal; October 2014 |
| Corporate Author |
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Thesis |
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| Publisher |
Springer International Publishing |
Place of Publication |
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Original Title |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-319-11757-7 |
Medium |
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| Area |
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Expedition |
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Conference |
ICIAR |
| Notes |
IAM; DAG; 600.060; 600.061; 600.077; 600.075 |
Approved |
no |
| Call Number |
Admin @ si @ BGB2014 |
Serial |
2559 |
| Permanent link to this record |
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| Author |
Simone Zini; Alex Gomez-Villa; Marco Buzzelli; Bartlomiej Twardowski; Andrew D. Bagdanov; Joost Van de Weijer |
| Title |
Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training |
Type |
Conference Article |
| Year |
2023 |
Publication |
11th International Conference on Learning Representations |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
Several recent works on self-supervised learning are trained by mapping different augmentations of the same image to the same feature representation. The data augmentations used are of crucial importance to the quality of learned feature representations. In this paper, we analyze how the color jitter traditionally used in data augmentation negatively impacts the quality of the color features in learned feature representations. To address this problem, we propose a more realistic, physics-based color data augmentation – which we call Planckian Jitter – that creates realistic variations in chromaticity and produces a model robust to illumination changes that can be commonly observed in real life, while maintaining the ability to discriminate image content based on color information. Experiments confirm that such a representation is complementary to the representations learned with the currently-used color jitter augmentation and that a simple concatenation leads to significant performance gains on a wide range of downstream datasets. In addition, we present a color sensitivity analysis that documents the impact of different training methods on model neurons and shows that the performance of the learned features is robust with respect to illuminant variations. |
| Address |
1 -5 May 2023, Kigali, Ruanda |
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| Series Editor |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ICLR |
| Notes |
LAMP; 600.147; 611.008; 5300006 |
Approved |
no |
| Call Number |
Admin @ si @ ZGB2023 |
Serial |
3820 |
| Permanent link to this record |
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| Author |
Xavier Perez; Cecilio Angulo; Sergio Escalera |
| Title |
Biologically Inspired Path Execution Using SURF Flow in Robot Navigation |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Work Conference on Artificial Neural Networks |
Abbreviated Journal |
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| Volume |
II |
Issue |
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Pages |
581--588 |
| Keywords |
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| Abstract |
An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo. |
| Address |
Malaga |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Summary Language |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-21497-4 |
Medium |
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| Area |
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Expedition |
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Conference |
IWANN |
| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ PAE2011b |
Serial |
1773 |
| Permanent link to this record |
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| Author |
Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras |
| Title |
The IIIA30 MObile Robot Object Recognition Datset |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th Portuguese Robotics Open |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones. |
| Address |
Lisboa |
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ISBN |
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Medium |
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Expedition |
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Conference |
Robotica |
| Notes |
RV;ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RAV2011 |
Serial |
1777 |
| Permanent link to this record |
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| Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
| Title |
Planar-Based Multispectral Stereo |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
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Issue |
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Pages |
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| Address |
Naples, Italy |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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Expedition |
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Conference |
QIRT |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ BLA2012 |
Serial |
2016 |
| Permanent link to this record |
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| Author |
Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo |
| Title |
A Novel SIFT-Like-Based Approach for FIR-VS Images Registration |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
Naples, Italy |
| Corporate Author |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
QIRT |
| Notes |
ADAS; TV |
Approved |
no |
| Call Number |
Admin @ si @ ABS2012 |
Serial |
2017 |
| Permanent link to this record |
