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Author |
Dimosthenis Karatzas;Ch. Lioutas |
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Title |
Software Package Development for Electron Diffraction Image Analysis |
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1998 |
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Proceedings of the XIV Solid State Physics National Conference |
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Ioannina, Greece |
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IAM @ iam @ KaL1998 |
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2045 |
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Author |
Mohammed Al Rawi; Dimosthenis Karatzas |
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Title |
On the Labeling Correctness in Computer Vision Datasets |
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2018 |
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Proceedings of the Workshop on Interactive Adaptive Learning, co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases |
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Image datasets have heavily been used to build computer vision systems.
These datasets are either manually or automatically labeled, which is a
problem as both labeling methods are prone to errors. To investigate this problem, we use a majority voting ensemble that combines the results from several Convolutional Neural Networks (CNNs). Majority voting ensembles not only enhance the overall performance, but can also be used to estimate the confidence level of each sample. We also examined Softmax as another form to estimate posterior probability. We have designed various experiments with a range of different ensembles built from one or different, or temporal/snapshot CNNs, which have been trained multiple times stochastically. We analyzed CIFAR10, CIFAR100, EMNIST, and SVHN datasets and we found quite a few incorrect
labels, both in the training and testing sets. We also present detailed confidence analysis on these datasets and we found that the ensemble is better than the Softmax when used estimate the per-sample confidence. This work thus proposes an approach that can be used to scrutinize and verify the labeling of computer vision datasets, which can later be applied to weakly/semi-supervised learning. We propose a measure, based on the Odds-Ratio, to quantify how many of these incorrectly classified labels are actually incorrectly labeled and how many of these are confusing. The proposed methods are easily scalable to larger datasets, like ImageNet, LSUN and SUN, as each CNN instance is trained for 60 epochs; or even faster, by implementing a temporal (snapshot) ensemble. |
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ECML-PKDDW |
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DAG; 600.121; 600.129 |
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Admin @ si @ RaK2018 |
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3144 |
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Author |
Ernest Valveny; Enric Marti |
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Title |
Recognition of lineal symbols in hand-written drawings using deformable template matching |
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1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes |
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DAG;IAM; |
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IAM @ iam @ VAM1999 |
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1658 |
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Author |
Josep Llados; Felipe Lumbreras; X. Varona |
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Title |
A multidocument platform for automatic reading of identity cards. |
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Miscellaneous |
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1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes. |
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Bilbao |
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ADAS;DAG |
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ADAS @ adas @ LLV1999 |
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7 |
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Author |
Ernest Valveny; B. Lamiroy |
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Title |
Automatic Generation of Browsable Technical Documents. |
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2002 |
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Proceedings of the Sixteenth International Conference on Pattern Recognition ICPR 2002: 188–191. |
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Quebec, Canada |
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DAG @ dag @ VaL2002 |
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301 |
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Author |
Ernest Valveny; Antonio Lopez |
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Title |
Numeral Recognition for Quality Control of Surgical Sachets |
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Miscellaneous |
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2003 |
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Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR´03), 379–383 |
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ADAS @ adas @ VaL2003 |
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423 |
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Author |
Oriol Ramos Terrades; Ernest Valveny |
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Title |
Radon Transform for Lineal Symbol Representation |
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Miscellaneous |
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2003 |
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Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR´03), 195–199 |
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DAG @ dag @ RaV2003d |
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406 |
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Author |
Ricardo Toledo; Ramon Baldrich; Ernest Valveny; Petia Radeva |
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Title |
Enhancing snakes for vessel detection in angiography images. |
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Miscellaneous |
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2002 |
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Proceedings of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002: 139–144. |
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MILAB;DAG;CIC;ADAS |
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BCNPCL @ bcnpcl @ TBV2002 |
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300 |
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Author |
Gemma Sanchez; Josep Llados; K. Tombre |
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An Algorithm to Recognize Graphical Textured Symbols using String Representations. |
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2001 |
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Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, :203–208. |
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DAG @ dag @ SLT2001a |
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163 |
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V. Chapaprieta; Ernest Valveny |
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Handwritten Digit Recognition Using Point Distribution Models. |
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2001 |
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Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 1:49–54. |
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DAG @ dag @ ChV2001 |
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83 |
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