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Author | Misael Rosales; Petia Radeva; J. Mauri; Oriol Pujol | ||||
Title | Simulation Model of Intravascular Ultrasound Images | Type | Miscellaneous | ||
Year | 2004 | Publication | MICCAI, 2004, Saint Melo, France | Abbreviated Journal | |
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Address | Springer Verlag | ||||
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ RRM2004b | Serial | 464 | ||
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Author | Misael Rosales | ||||
Title | Empirical Simulation Moldel of Intravascular Ultrasound | Type | Miscellaneous | ||
Year | 2002 | Publication | Director: P. Radeva, Master Thesis. | Abbreviated Journal | |
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Address | CVC (UAB) | ||||
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Notes | Approved | no | |||
Call Number | Admin @ si @ Ros2002 | Serial | 323 | ||
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Author | Miquel Ferrer; Robert Benavente; Ernest Valveny; J. Garcia; Agata Lapedriza; Gemma Sanchez | ||||
Title | Aprendizaje Cooperativo Aplicado a la Docencia de las Asignaturas de Programacion en Ingenieria Informatica | Type | Miscellaneous | ||
Year | 2008 | Publication | Octava Jornada sobre Aprendizaje Cooperativo, 41–46 | Abbreviated Journal | |
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Address | Lleida (Spain). | ||||
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Notes | OR;DAG;CIC;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ FBV2008 | Serial | 955 | ||
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Author | Mikhail Mozerov; V. Kober; I.A. Ovseyevich | ||||
Title | A Stereo Matching Algorithm with Global Smoothness Criterion | Type | Miscellaneous | ||
Year | 2006 | Publication | Topical Meeting on Optoinformatics / Information Photonics, 133–135 | Abbreviated Journal | |
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Address | Saint-Petersburg (Russia) | ||||
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Notes | ISE | Approved | no | ||
Call Number | ISE @ ise @ MKO2006 | Serial | 675 | ||
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Author | Mikel Menta; Adriana Romero; Joost Van de Weijer | ||||
Title | Learning to adapt class-specific features across domains for semantic segmentation | Type | Miscellaneous | ||
Year | 2020 | Publication | Arxiv | Abbreviated Journal | |
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Abstract | arXiv:2001.08311
Recent advances in unsupervised domain adaptation have shown the effectiveness of adversarial training to adapt features across domains, endowing neural networks with the capability of being tested on a target domain without requiring any training annotations in this domain. The great majority of existing domain adaptation models rely on image translation networks, which often contain a huge amount of domain-specific parameters. Additionally, the feature adaptation step often happens globally, at a coarse level, hindering its applicability to tasks such as semantic segmentation, where details are of crucial importance to provide sharp results. In this thesis, we present a novel architecture, which learns to adapt features across domains by taking into account per class information. To that aim, we design a conditional pixel-wise discriminator network, whose output is conditioned on the segmentation masks. Moreover, following recent advances in image translation, we adopt the recently introduced StarGAN architecture as image translation backbone, since it is able to perform translations across multiple domains by means of a single generator network. Preliminary results on a segmentation task designed to assess the effectiveness of the proposed approach highlight the potential of the model, improving upon strong baselines and alternative designs. |
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Notes | LAMP; 600.120 | Approved | no | ||
Call Number | Admin @ si @ MRW2020 | Serial | 3545 | ||
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Author | Michael Villamizar; A. Sanfeliu; Juan Andrade | ||||
Title | Computation of Rotation Local Invariant Features using the Integral Image for Real Time Object Detection | Type | Miscellaneous | ||
Year | 2006 | Publication | 18th International Conference on Pattern Recognition, 81–85 | Abbreviated Journal | |
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Address | Hong Kong | ||||
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Notes | Approved | no | |||
Call Number | Admin @ si @ VSA2006a | Serial | 663 | ||
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Author | Michael Villamizar; A. Sanfeliu; Juan Andrade | ||||
Title | Orientation Invariant Features for Multiclass Object Recognition | Type | Miscellaneous | ||
Year | 2006 | Publication | 11th Iberoamerican Congress on Pattern Recognition (CIARP´06), LNCS 4225: 655–664 | Abbreviated Journal | |
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Address | Cancun (Mexico) | ||||
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Notes | Approved | no | |||
Call Number | Admin @ si @ VSA2006b | Serial | 664 | ||
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Author | Mert Kilickaya; Joost van de Weijer; Yuki M. Asano | ||||
Title | Towards Label-Efficient Incremental Learning: A Survey | Type | Miscellaneous | ||
Year | 2023 | Publication | Arxiv | Abbreviated Journal | |
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Abstract | The current dominant paradigm when building a machine learning model is to iterate over a dataset over and over until convergence. Such an approach is non-incremental, as it assumes access to all images of all categories at once. However, for many applications, non-incremental learning is unrealistic. To that end, researchers study incremental learning, where a learner is required to adapt to an incoming stream of data with a varying distribution while preventing forgetting of past knowledge. Significant progress has been made, however, the vast majority of works focus on the fully supervised setting, making these algorithms label-hungry thus limiting their real-life deployment. To that end, in this paper, we make the first attempt to survey recently growing interest in label-efficient incremental learning. We identify three subdivisions, namely semi-, few-shot- and self-supervised learning to reduce labeling efforts. Finally, we identify novel directions that can further enhance label-efficiency and improve incremental learning scalability. Project website: this https URL. | ||||
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Notes | LAMP | Approved | no | ||
Call Number | Admin @ si @ KWA2023 | Serial | 3994 | ||
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Author | Md. Mostafa Kamal Sarker; Mohammed Jabreel; Hatem A. Rashwan; Syeda Furruka Banu; Antonio Moreno; Petia Radeva; Domenec Puig | ||||
Title | CuisineNet: Food Attributes Classification using Multi-scale Convolution Network. | Type | Miscellaneous | ||
Year | 2018 | Publication | Arxiv | Abbreviated Journal | |
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Abstract | Diversity of food and its attributes represents the culinary habits of peoples from different countries. Thus, this paper addresses the problem of identifying food culture of people around the world and its flavor by classifying two main food attributes, cuisine and flavor. A deep learning model based on multi-scale convotuional networks is proposed for extracting more accurate features from input images. The aggregation of multi-scale convolution layers with different kernel size is also used for weighting the features results from different scales. In addition, a joint loss function based on Negative Log Likelihood (NLL) is used to fit the model probability to multi labeled classes for multi-modal classification task. Furthermore, this work provides a new dataset for food attributes, so-called Yummly48K, extracted from the popular food website, Yummly. Our model is assessed on the constructed Yummly48K dataset. The experimental results show that our proposed method yields 65% and 62% average F1 score on validation and test set which outperforming the state-of-the-art models. | ||||
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Notes | MILAB; no proj | Approved | no | ||
Call Number | Admin @ si @ KJR2018 | Serial | 3235 | ||
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Author | Md. Mostafa Kamal Sarker; Hatem A. Rashwan; Mohamed Abdel-Nasser; Vivek Kumar Singh; Syeda Furruka Banu; Farhan Akram; Forhad U. H. Chowdhury; Kabir Ahmed Choudhury; Sylvie Chambon; Petia Radeva; Domenec Puig | ||||
Title | MobileGAN: Skin Lesion Segmentation Using a Lightweight Generative Adversarial Network | Type | Miscellaneous | ||
Year | 2019 | Publication | Arxiv | Abbreviated Journal | |
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Abstract | CoRR abs/1907.00856
Skin lesion segmentation in dermoscopic images is a challenge due to their blurry and irregular boundaries. Most of the segmentation approaches based on deep learning are time and memory consuming due to the hundreds of millions of parameters. Consequently, it is difficult to apply them to real dermatoscope devices with limited GPU and memory resources. In this paper, we propose a lightweight and efficient Generative Adversarial Networks (GAN) model, called MobileGAN for skin lesion segmentation. More precisely, the MobileGAN combines 1D non-bottleneck factorization networks with position and channel attention modules in a GAN model. The proposed model is evaluated on the test dataset of the ISBI 2017 challenges and the validation dataset of ISIC 2018 challenges. Although the proposed network has only 2.35 millions of parameters, it is still comparable with the state-of-the-art. The experimental results show that our MobileGAN obtains comparable performance with an accuracy of 97.61%. |
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Notes | MILAB; no menciona | Approved | no | ||
Call Number | Admin @ si @ MRA2019 | Serial | 3384 | ||
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Author | Maya Dimitrova; Petia Radeva; David Rotger; D. Boyadjiev; Juan J. Villanueva | ||||
Title | Advanced Cardiological Diagnosis via Intelligent Image Analysis | Type | Miscellaneous | ||
Year | 2004 | Publication | Abbreviated Journal | ||
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Address | Varna (Bulgaria) | ||||
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ DRR2004 | Serial | 477 | ||
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Author | Maya Dimitrova; N. Kushmerick; Petia Radeva; Juan J. Villanueva | ||||
Title | User Assesment of a Visual Genre Classifier | Type | Miscellaneous | ||
Year | 2003 | Publication | Proceedings of the 3rd IASTED Int. Conference Visualization, Imaging and Image Processing | Abbreviated Journal | |
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ DKR2003 | Serial | 372 | ||
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Author | Maya Dimitrova; I. Terziev; Petia Radeva; Juan J. Villanueva | ||||
Title | Java-Servlet Technology for Building New Web Document Classifiers | Type | Miscellaneous | ||
Year | 2004 | Publication | Abbreviated Journal | ||
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Address | Varna (Bulgaria) | ||||
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ DTR2004 | Serial | 476 | ||
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Author | Maya Dimitrova; Ch. Roumenin; Petia Radeva; David Rotger; Juan J. Villanueva | ||||
Title | Multimodal Intelligent System for Cardiovascular Diagnosis | Type | Miscellaneous | ||
Year | 2003 | Publication | Automation and Informatics, any XXXVII, num. 3 | Abbreviated Journal | |
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ DRR2003 | Serial | 374 | ||
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Author | Matthias S. Keil; Jordi Vitria | ||||
Title | Does the brain generate representations of smooth brightness gradients? A novel account for Mach bands, Chevreul’s illusion, and a variant of the Ehrenstein disk | Type | Miscellaneous | ||
Year | 2005 | Publication | European Conference on Visual Perception | Abbreviated Journal | |
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Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ KeV2005b | Serial | 607 | ||
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