|
Records |
Links ![sorted by URL field, ascending order (up)](img/sort_asc.gif) |
|
Author |
Dustin Carrion Ojeda; Hong Chen; Adrian El Baz; Sergio Escalera; Chaoyu Guan; Isabelle Guyon; Ihsan Ullah; Xin Wang; Wenwu Zhu |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
NeurIPS’22 Cross-Domain MetaDL competition: Design and baseline results |
Type |
Conference Article |
|
Year |
2022 |
Publication |
Understanding Social Behavior in Dyadic and Small Group Interactions |
Abbreviated Journal |
|
|
|
Volume |
191 |
Issue |
|
Pages |
24-37 |
|
|
Keywords |
|
|
|
Abstract |
We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on “cross-domain” meta-learning. Meta-learning aims to leverage experience gained from previous tasks to solve new tasks efficiently (i.e., with better performance, little training data, and/or modest computational resources). While previous challenges in the series focused on within-domain few-shot learning problems, with the aim of learning efficiently N-way k-shot tasks (i.e., N class classification problems with k training examples), this competition challenges the participants to solve “any-way” and “any-shot” problems drawn from various domains (healthcare, ecology, biology, manufacturing, and others), chosen for their humanitarian and societal impact. To that end, we created Meta-Album, a meta-dataset of 40 image classification datasets from 10 domains, from which we carve out tasks with any number of “ways” (within the range 2-20) and any number of “shots” (within the range 1-20). The competition is with code submission, fully blind-tested on the CodaLab challenge platform. The code of the winners will be open-sourced, enabling the deployment of automated machine learning solutions for few-shot image classification across several domains. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
PMLR |
|
|
Notes |
HUPBA; no menciona |
Approved |
no |
|
|
Call Number |
Admin @ si @ CCB2022 |
Serial |
3802 |
|
Permanent link to this record |
|
|
|
|
Author |
Shiqi Yang; Yaxing Wang; Joost Van de Weijer; Luis Herranz; Shangling Jui |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation |
Type |
Conference Article |
|
Year |
2021 |
Publication |
Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Domain adaptation (DA) aims to alleviate the domain shift between source domain and target domain. Most DA methods require access to the source data, but often that is not possible (e.g. due to data privacy or intellectual property). In this paper, we address the challenging source-free domain adaptation (SFDA) problem, where the source pretrained model is adapted to the target domain in the absence of source data. Our method is based on the observation that target data, which might no longer align with the source domain classifier, still forms clear clusters. We capture this intrinsic structure by defining local affinity of the target data, and encourage label consistency among data with high local affinity. We observe that higher affinity should be assigned to reciprocal neighbors, and propose a self regularization loss to decrease the negative impact of noisy neighbors. Furthermore, to aggregate information with more context, we consider expanded neighborhoods with small affinity values. In the experimental results we verify that the inherent structure of the target features is an important source of information for domain adaptation. We demonstrate that this local structure can be efficiently captured by considering the local neighbors, the reciprocal neighbors, and the expanded neighborhood. Finally, we achieve state-of-the-art performance on several 2D image and 3D point cloud recognition datasets. Code is available in https://github.com/Albert0147/SFDA_neighbors. |
|
|
Address |
Online; December 7-10, 2021 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
NIPS |
|
|
Notes |
LAMP; 600.147; 600.141 |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
3691 |
|
Permanent link to this record |
|
|
|
|
Author |
O.F.Ahmad; Y.Mori; M.Misawa; S.Kudo; J.T.Anderson; Jorge Bernal |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method |
Type |
Journal Article |
|
Year |
2021 |
Publication |
Endoscopy |
Abbreviated Journal |
END |
|
|
Volume |
53 |
Issue |
9 |
Pages |
893-901 |
|
|
Keywords |
|
|
|
Abstract |
BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. METHODS : An established modified Delphi approach for research priority setting was used. Fifteen international experts, including endoscopists and translational computer scientists/engineers, from nine countries participated in an online survey over 9 months. Questions related to AI implementation in colonoscopy were generated as a long-list in the first round, and then scored in two subsequent rounds to identify the top 10 research questions. RESULTS : The top 10 ranked questions were categorized into five themes. Theme 1: clinical trial design/end points (4 questions), related to optimum trial designs for polyp detection and characterization, determining the optimal end points for evaluation of AI, and demonstrating impact on interval cancer rates. Theme 2: technological developments (3 questions), including improving detection of more challenging and advanced lesions, reduction of false-positive rates, and minimizing latency. Theme 3: clinical adoption/integration (1 question), concerning the effective combination of detection and characterization into one workflow. Theme 4: data access/annotation (1 question), concerning more efficient or automated data annotation methods to reduce the burden on human experts. Theme 5: regulatory approval (1 question), related to making regulatory approval processes more efficient. CONCLUSIONS : This is the first reported international research priority setting exercise for AI in colonoscopy. The study findings should be used as a framework to guide future research with key stakeholders to accelerate the clinical implementation of AI in endoscopy. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ AMM2021 |
Serial |
3670 |
|
Permanent link to this record |
|
|
|
|
Author |
Diana Ramirez Cifuentes; Ana Freire; Ricardo Baeza Yates; Nadia Sanz Lamora; Aida Alvarez; Alexandre Gonzalez; Meritxell Lozano; Roger Llobet; Diego Velazquez; Josep M. Gonfaus; Jordi Gonzalez |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Characterization of Anorexia Nervosa on Social Media: Textual, Visual, Relational, Behavioral, and Demographical Analysis |
Type |
Journal Article |
|
Year |
2021 |
Publication |
Journal of Medical Internet Research |
Abbreviated Journal |
JMIR |
|
|
Volume |
23 |
Issue |
7 |
Pages |
e25925 |
|
|
Keywords |
|
|
|
Abstract |
Background: Eating disorders are psychological conditions characterized by unhealthy eating habits. Anorexia nervosa (AN) is defined as the belief of being overweight despite being dangerously underweight. The psychological signs involve emotional and behavioral issues. There is evidence that signs and symptoms can manifest on social media, wherein both harmful and beneficial content is shared daily. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ RFB2021 |
Serial |
3665 |
|
Permanent link to this record |
|
|
|
|
Author |
Giuseppe Pezzano; Oliver Diaz; Vicent Ribas Ripoll; Petia Radeva |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
CoLe-CNN+: Context learning – Convolutional neural network for COVID-19-Ground-Glass-Opacities detection and segmentation |
Type |
Journal Article |
|
Year |
2021 |
Publication |
Computers in Biology and Medicine |
Abbreviated Journal |
CBM |
|
|
Volume |
136 |
Issue |
|
Pages |
104689 |
|
|
Keywords |
|
|
|
Abstract |
The most common tool for population-wide COVID-19 identification is the Reverse Transcription-Polymerase Chain Reaction test that detects the presence of the virus in the throat (or sputum) in swab samples. This test has a sensitivity between 59% and 71%. However, this test does not provide precise information regarding the extension of the pulmonary infection. Moreover, it has been proven that through the reading of a computed tomography (CT) scan, a clinician can provide a more complete perspective of the severity of the disease. Therefore, we propose a comprehensive system for fully-automated COVID-19 detection and lesion segmentation from CT scans, powered by deep learning strategies to support decision-making process for the diagnosis of COVID-19. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MILAB; no menciona |
Approved |
no |
|
|
Call Number |
Admin @ si @ PDR2021 |
Serial |
3635 |
|
Permanent link to this record |
|
|
|
|
Author |
Carlos Martin-Isla; Victor M Campello; Cristian Izquierdo; Kaisar Kushibar; Carla Sendra Balcells; Polyxeni Gkontra; Alireza Sojoudi; Mitchell J Fulton; Tewodros Weldebirhan Arega; Kumaradevan Punithakumar; Lei Li; Xiaowu Sun; Yasmina Al Khalil; Di Liu; Sana Jabbar; Sandro Queiros; Francesco Galati; Moona Mazher; Zheyao Gao; Marcel Beetz; Lennart Tautz; Christoforos Galazis; Marta Varela; Markus Hullebrand; Vicente Grau; Xiahai Zhuang; Domenec Puig; Maria A Zuluaga; Hassan Mohy Ud Din; Dimitris Metaxas; Marcel Breeuwer; Rob J van der Geest; Michelle Noga; Stephanie Bricq; Mark E Rentschler; Andrea Guala; Steffen E Petersen; Sergio Escalera; Jose F Rodriguez Palomares; Karim Lekadir |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&ms Challenge |
Type |
Journal Article |
|
Year |
2023 |
Publication |
IEEE Journal of Biomedical and Health Informatics |
Abbreviated Journal |
JBHI |
|
|
Volume |
27 |
Issue |
7 |
Pages |
3302-3313 |
|
|
Keywords |
|
|
|
Abstract |
In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of the right ventricle is challenging due to its highly complex shape and ill-defined borders. Hence, there is a need for new methods to handle such structure's geometrical and textural complexities, notably in the presence of pathologies such as Dilated Right Ventricle, Tricuspid Regurgitation, Arrhythmogenesis, Tetralogy of Fallot, and Inter-atrial Communication. The last MICCAI challenge on right ventricle segmentation was held in 2012 and included only 48 cases from a single clinical center. As part of the 12th Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2021), the M&Ms-2 challenge was organized to promote the interest of the research community around right ventricle segmentation in multi-disease, multi-view, and multi-center cardiac MRI. Three hundred sixty CMR cases, including short-axis and long-axis 4-chamber views, were collected from three Spanish hospitals using nine different scanners from three different vendors, and included a diverse set of right and left ventricle pathologies. The solutions provided by the participants show that nnU-Net achieved the best results overall. However, multi-view approaches were able to capture additional information, highlighting the need to integrate multiple cardiac diseases, views, scanners, and acquisition protocols to produce reliable automatic cardiac segmentation algorithms. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
HUPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ MCI2023 |
Serial |
3880 |
|
Permanent link to this record |
|
|
|
|
Author |
D. Seron; F. Moreso; C. Gratin; Jordi Vitria; E. Condom |
![goto web page url](img/www.gif)
|
|
Title |
Automated classification of renal interstitium and tubules by local texture analysis and a neural network |
Type |
Journal Article |
|
Year |
1996 |
Publication |
Analytical and Quantitative Cytology and Histology |
Abbreviated Journal |
|
|
|
Volume |
18 |
Issue |
5 |
Pages |
410-9, PMID: 8908314 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ SMG1996 |
Serial |
76 |
|
Permanent link to this record |
|
|
|
|
Author |
Marta Ligero; Alonso Garcia Ruiz; Cristina Viaplana; Guillermo Villacampa; Maria V Raciti; Jaid Landa; Ignacio Matos; Juan Martin Liberal; Maria Ochoa de Olza; Cinta Hierro; Joaquin Mateo; Macarena Gonzalez; Rafael Morales Barrera; Cristina Suarez; Jordi Rodon; Elena Elez; Irene Braña; Eva Muñoz-Couselo; Ana Oaknin; Roberta Fasani; Paolo Nuciforo; Debora Gil; Carlota Rubio Perez; Joan Seoane; Enriqueta Felip; Manuel Escobar; Josep Tabernero; Joan Carles; Rodrigo Dienstmann; Elena Garralda; Raquel Perez Lopez |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
A CT-based radiomics signature is associated with response to immune checkpoint inhibitors in advanced solid tumors |
Type |
Journal Article |
|
Year |
2021 |
Publication |
Radiology |
Abbreviated Journal |
|
|
|
Volume |
299 |
Issue |
1 |
Pages |
109-119 |
|
|
Keywords |
|
|
|
Abstract |
Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; 600.145 |
Approved |
no |
|
|
Call Number |
Admin @ si @ LGV2021 |
Serial |
3593 |
|
Permanent link to this record |
|
|
|
|
Author |
G. Gasbarri; Matias Bilkis; E. Roda Salichs; J. Calsamiglia |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Sequential hypothesis testing for continuously-monitored quantum systems |
Type |
Journal Article |
|
Year |
2024 |
Publication |
Quantum |
Abbreviated Journal |
|
|
|
Volume |
8 |
Issue |
1289 |
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
We consider a quantum system that is being continuously monitored, giving rise to a measurement signal. From such a stream of data, information needs to be inferred about the underlying system's dynamics. Here we focus on hypothesis testing problems and put forward the usage of sequential strategies where the signal is analyzed in real time, allowing the experiment to be concluded as soon as the underlying hypothesis can be identified with a certified prescribed success probability. We analyze the performance of sequential tests by studying the stopping-time behavior, showing a considerable advantage over currently-used strategies based on a fixed predetermined measurement time. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
xxxx |
Approved |
no |
|
|
Call Number |
Admin @ si @ GBR2024 |
Serial |
3847 |
|
Permanent link to this record |
|
|
|
|
Author |
Ali Furkan Biten; Ruben Tito; Andres Mafla; Lluis Gomez; Marçal Rusiñol; M. Mathew; C.V. Jawahar; Ernest Valveny; Dimosthenis Karatzas |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
ICDAR 2019 Competition on Scene Text Visual Question Answering |
Type |
Conference Article |
|
Year |
2019 |
Publication |
3rd Workshop on Closing the Loop Between Vision and Language, in conjunction with ICCV2019 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
This paper presents final results of ICDAR 2019 Scene Text Visual Question Answering competition (ST-VQA). ST-VQA introduces an important aspect that is not addressed
by any Visual Question Answering system up to date, namely the incorporation of scene text to answer questions asked about an image. The competition introduces a new dataset comprising 23, 038 images annotated with 31, 791 question / answer pairs where the answer is always grounded on text instances present in the image. The images are taken from 7 different public computer vision datasets, covering a wide range of scenarios.
The competition was structured in three tasks of increasing difficulty, that require reading the text in a scene and understanding it in the context of the scene, to correctly answer a given question. A novel evaluation metric is presented, which elegantly assesses both key capabilities expected from an optimal model: text recognition and image understanding. A detailed analysis of results from different participants is showcased, which provides insight into the current capabilities of VQA systems that can read. We firmly believe the dataset proposed in this challenge will be an important milestone to consider towards a path of more robust and general models that
can exploit scene text to achieve holistic image understanding. |
|
|
Address |
Sydney; Australia; September 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CLVL |
|
|
Notes |
DAG; 600.129; 601.338; 600.135; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ BTM2019a |
Serial |
3284 |
|
Permanent link to this record |
|
|
|
|
Author |
Ali Furkan Biten; Ruben Tito; Lluis Gomez; Ernest Valveny; Dimosthenis Karatzas |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
OCR-IDL: OCR Annotations for Industry Document Library Dataset |
Type |
Conference Article |
|
Year |
2022 |
Publication |
ECCV Workshop on Text in Everything |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Pretraining has proven successful in Document Intelligence tasks where deluge of documents are used to pretrain the models only later to be finetuned on downstream tasks. One of the problems of the pretraining approaches is the inconsistent usage of pretraining data with different OCR engines leading to incomparable results between models. In other words, it is not obvious whether the performance gain is coming from diverse usage of amount of data and distinct OCR engines or from the proposed models. To remedy the problem, we make public the OCR annotations for IDL documents using commercial OCR engine given their superior performance over open source OCR models. The contributed dataset (OCR-IDL) has an estimated monetary value over 20K US$. It is our hope that OCR-IDL can be a starting point for future works on Document Intelligence. All of our data and its collection process with the annotations can be found in this https URL. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ECCV |
|
|
Notes |
DAG; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ BTG2022 |
Serial |
3817 |
|
Permanent link to this record |
|
|
|
|
Author |
Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva |
![goto web page url](img/www.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
On the Design of Low Redundancy Error-Correcting Output Codes |
Type |
Book Chapter |
|
Year |
2011 |
Publication |
Ensembles in Machine Learning Applications |
Abbreviated Journal |
|
|
|
Volume |
373 |
Issue |
2 |
Pages |
21-38 |
|
|
Keywords |
|
|
|
Abstract |
The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1860-949X |
ISBN |
978-3-642-22909-1 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
|
|
Call Number |
Admin @ si @ BEB2011b |
Serial |
1886 |
|
Permanent link to this record |
|
|
|
|
Author |
J.Poujol; Cristhian A. Aguilera-Carrasco; E.Danos; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Visible-Thermal Fusion based Monocular Visual Odometry |
Type |
Conference Article |
|
Year |
2015 |
Publication |
2nd Iberian Robotics Conference ROBOT2015 |
Abbreviated Journal |
|
|
|
Volume |
417 |
Issue |
|
Pages |
517-528 |
|
|
Keywords |
Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion. |
|
|
Abstract |
The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained
representations are evaluated under a visual odometry framework, highlighting
their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach. |
|
|
Address |
Lisboa; Portugal; November 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
2194-5357 |
ISBN |
978-3-319-27145-3 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ROBOT |
|
|
Notes |
ADAS; 600.076; 600.086 |
Approved |
no |
|
|
Call Number |
Admin @ si @ PAD2015 |
Serial |
2663 |
|
Permanent link to this record |
|
|
|
|
Author |
Mariella Dimiccoli; Petia Radeva |
![goto web page url](img/www.gif)
|
|
Title |
Lifelogging in the era of outstanding digitization |
Type |
Conference Article |
|
Year |
2015 |
Publication |
International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior. |
|
|
Address |
Verliko Tarmovo; Bulgaria; September 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
DiPP |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @DiR2016 |
Serial |
2792 |
|
Permanent link to this record |
|
|
|
|
Author |
Hugo Bertiche; Niloy J Mitra; Kuldeep Kulkarni; Chun Hao Paul Huang; Tuanfeng Y Wang; Meysam Madadi; Sergio Escalera; Duygu Ceylan |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Blowing in the Wind: CycleNet for Human Cinemagraphs from Still Images |
Type |
Conference Article |
|
Year |
2023 |
Publication |
36th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
459-468 |
|
|
Keywords |
|
|
|
Abstract |
Cinemagraphs are short looping videos created by adding subtle motions to a static image. This kind of media is popular and engaging. However, automatic generation of cinemagraphs is an underexplored area and current solutions require tedious low-level manual authoring by artists. In this paper, we present an automatic method that allows generating human cinemagraphs from single RGB images. We investigate the problem in the context of dressed humans under the wind. At the core of our method is a novel cyclic neural network that produces looping cinemagraphs for the target loop duration. To circumvent the problem of collecting real data, we demonstrate that it is possible, by working in the image normal space, to learn garment motion dynamics on synthetic data and generalize to real data. We evaluate our method on both synthetic and real data and demonstrate that it is possible to create compelling and plausible cinemagraphs from single RGB images. |
|
|
Address |
Vancouver; Canada; June 2023 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CVPR |
|
|
Notes |
HUPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ BMK2023 |
Serial |
3921 |
|
Permanent link to this record |