| Records |
| Author |
Patricia Suarez; Angel Sappa; Boris X. Vintimilla |
| Title |
Colorizing Infrared Images through a Triplet Conditional DCGAN Architecture |
Type |
Conference Article |
| Year |
2017 |
Publication |
19th international conference on image analysis and processing |
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| Keywords |
CNN in Multispectral Imaging; Image Colorization |
| Abstract |
This paper focuses on near infrared (NIR) image colorization by using a Conditional Deep Convolutional Generative Adversarial Network (CDCGAN) architecture model. The proposed architecture is based on the usage of a conditional probabilistic generative model. Firstly, it learns to colorize the given input image, by using a triplet model architecture that tackle every channel in an independent way. In the proposed model, the nal layer of red channel consider the infrared image to enhance the details, resulting in a sharp RGB image. Then, in the second stage, a discriminative model is used to estimate the probability that the generated image came from the training dataset, rather than the image automatically generated. Experimental results with a large set of real images are provided showing the validity of the proposed approach. Additionally, the proposed approach is compared with a state of the art approach showing better results. |
| Address |
Catania; Italy; September 2017 |
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ICIAP |
| Notes |
ADAS; MSIAU; 600.086; 600.122; 600.118 |
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no |
| Call Number |
Admin @ si @ SSV2017c |
Serial |
3016 |
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| Author |
Marc Oliu; Sarah Adel Bargal; Stan Sclaroff; Xavier Baro; Sergio Escalera |
| Title |
Multi-varied Cumulative Alignment for Domain Adaptation |
Type |
Conference Article |
| Year |
2022 |
Publication |
6th International Conference on Image Analysis and Processing |
Abbreviated Journal |
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| Volume |
13232 |
Issue |
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Pages |
324–334 |
| Keywords |
Domain Adaptation; Computer vision; Neural networks |
| Abstract |
Domain Adaptation methods can be classified into two basic families of approaches: non-parametric and parametric. Non-parametric approaches depend on statistical indicators such as feature covariances to minimize the domain shift. Non-parametric approaches tend to be fast to compute and require no additional parameters, but they are unable to leverage probability density functions with complex internal structures. Parametric approaches, on the other hand, use models of the probability distributions as surrogates in minimizing the domain shift, but they require additional trainable parameters to model these distributions. In this work, we propose a new statistical approach to minimizing the domain shift based on stochastically projecting and evaluating the cumulative density function in both domains. As with non-parametric approaches, there are no additional trainable parameters. As with parametric approaches, the internal structure of both domains’ probability distributions is considered, thus leveraging a higher amount of information when reducing the domain shift. Evaluation on standard datasets used for Domain Adaptation shows better performance of the proposed model compared to non-parametric approaches while being competitive with parametric ones. (Code available at: https://github.com/moliusimon/mca). |
| Address |
Indonesia; October 2022 |
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ICIAP |
| Notes |
HuPBA; no menciona |
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no |
| Call Number |
Admin @ si @ OAS2022 |
Serial |
3777 |
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| Author |
Patricia Suarez; Dario Carpio; Angel Sappa |
| Title |
A Deep Learning Based Approach for Synthesizing Realistic Depth Maps |
Type |
Conference Article |
| Year |
2023 |
Publication |
22nd International Conference on Image Analysis and Processing |
Abbreviated Journal |
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| Volume |
14234 |
Issue |
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Pages |
369–380 |
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| Abstract |
This paper presents a novel cycle generative adversarial network (CycleGAN) architecture for synthesizing high-quality depth maps from a given monocular image. The proposed architecture uses multiple loss functions, including cycle consistency, contrastive, identity, and least square losses, to enable the generation of realistic and high-fidelity depth maps. The proposed approach addresses this challenge by synthesizing depth maps from RGB images without requiring paired training data. Comparisons with several state-of-the-art approaches are provided showing the proposed approach overcome other approaches both in terms of quantitative metrics and visual quality. |
| Address |
Udine; Italia; Setember 2023 |
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ICIAP |
| Notes |
MSIAU |
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no |
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Admin @ si @ SCS2023a |
Serial |
3968 |
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| Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
| Title |
Morphology Based Handwritten Line Segmentation using Foreground and Background Information |
Type |
Conference Article |
| Year |
2008 |
Publication |
International Conference on Frontiers in Handwriting Recognition, |
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Issue |
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Pages |
241–246 |
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| Address |
Montreal (Canada) |
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Conference |
ICFHR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ RPL2008a |
Serial |
1050 |
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| Author |
Jose Antonio Rodriguez; Florent Perronnin |
| Title |
Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents |
Type |
Conference Article |
| Year |
2008 |
Publication |
International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
7–12 |
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| Address |
Montreal (Canada) |
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ICFHR |
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no |
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Admin @ si @ RoP2008b |
Serial |
1066 |
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| Author |
Jose Antonio Rodriguez; Florent Perronnin |
| Title |
Score Normalization for Hmm-based Word Spotting Using Universal Background Model |
Type |
Conference Article |
| Year |
2008 |
Publication |
International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
82–87 |
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| Abstract |
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| Address |
Montreal (Canada) |
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Place of Publication |
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Conference |
ICFHR |
| Notes |
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Approved |
no |
| Call Number |
Admin @ si @ RoP2008c |
Serial |
1067 |
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| Author |
Alicia Fornes; Josep Llados |
| Title |
A Symbol-dependent Writer Identifcation Approach in Old Handwritten Music Scores |
Type |
Conference Article |
| Year |
2010 |
Publication |
12th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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Issue |
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Pages |
634 - 639 |
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| Abstract |
Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we introduce a symbol-dependent approach for identifying the writer of old music scores, which is based on two symbol recognition methods. The main idea is to use the Blurred Shape Model descriptor and a DTW-based method for detecting, recognizing and describing the music clefs and notes. The proposed approach has been evaluated in a database of old music scores, achieving very high writer identification rates. |
| Address |
Kolkata (India) |
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ISBN |
978-1-4244-8353-2 |
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Conference |
ICFHR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ FoL2010 |
Serial |
1321 |
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| Author |
Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny |
| Title |
A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
453-458 |
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| Abstract |
In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase. |
| Address |
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ISBN |
978-1-4673-2262-1 |
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ICFHR |
| Notes |
DAG |
Approved |
no |
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DAG @ dag @ AFF2012 |
Serial |
1983 |
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| Author |
Marçal Rusiñol; Josep Llados |
| Title |
The Role of the Users in Handwritten Word Spotting Applications: Query Fusion and Relevance Feedback |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
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Issue |
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Pages |
55-60 |
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In this paper we present the importance of including the user in the loop in a handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and a baseline word spotting approach based on a bag-of-visual-words model. |
| Address |
Bari, Italy |
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Place of Publication |
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ISBN |
978-1-4673-2262-1 |
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Conference |
ICFHR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RuL2012 |
Serial |
2054 |
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| Author |
Volkmar Frinken; Markus Baumgartner; Andreas Fischer; Horst Bunke |
| Title |
Semi-Supervised Learning for Cursive Handwriting Recognition using Keyword Spotting |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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Issue |
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Pages |
49-54 |
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State-of-the-art handwriting recognition systems are learning-based systems that require large sets of training data. The creation of training data, and consequently the creation of a well-performing recognition system, requires therefore a substantial amount of human work. This can be reduced with semi-supervised learning, which uses unlabeled text lines for training as well. Current approaches estimate the correct transcription of the unlabeled data via handwriting recognition which is not only extremely demanding as far as computational costs are concerned but also requires a good model of the target language. In this paper, we propose a different approach that makes use of keyword spotting, which is significantly faster and does not need any language model. In a set of experiments we demonstrate its superiority over existing approaches. |
| Address |
Bari, Italy |
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10.1109/ICFHR.2012.268 |
ISBN |
978-1-4673-2262-1 |
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ICFHR |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ FBF2012 |
Serial |
2055 |
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| Author |
Emanuel Indermühle; Volkmar Frinken; Horst Bunke |
| Title |
Mode Detection in Online Handwritten Documents using BLSTM Neural Networks |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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Issue |
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Pages |
302-307 |
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Mode detection in online handwritten documents refers to the process of distinguishing different types of contents, such as text, formulas, diagrams, or tables, one from another. In this paper a new approach to mode detection is proposed that uses bidirectional long-short term memory (BLSTM) neural networks. The BLSTM neural network is a novel type of recursive neural network that has been successfully applied in speech and handwriting recognition. In this paper we show that it has the potential to significantly outperform traditional methods for mode detection, which are usually based on stroke classification. As a further advantage over previous approaches, the proposed system is trainable and does not rely on user-defined heuristics. Moreover, it can be easily adapted to new or additional types of modes by just providing the system with new training data. |
| Address |
Bari, italy |
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978-1-4673-2262-1 |
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ICFHR |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ IFB2012 |
Serial |
2056 |
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| Author |
David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha |
| Title |
On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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Issue |
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Pages |
763-768 |
| Keywords |
document image processing;handwritten character recognition;history;image segmentation;Spanish document;historical document;line segmentation;old handwritten document;old manuscript;word segmentation;Bifurcation;Dynamic programming;Handwriting recognition;Image segmentation;Measurement;Noise;Skeleton;Segmentation;document analysis;document and text processing;handwriting analysis;heuristics;path-finding |
| Abstract |
he objective of this work is to show the importance of a good line segmentation to obtain better results in the segmentation of words of historical documents. We have used the approach developed by Manmatha and Rothfeder [1] to segment words in old handwritten documents. In their work the lines of the documents are extracted using projections. In this work, we have developed an approach to segment lines more efficiently. The new line segmentation algorithm tackles with skewed, touching and noisy lines, so it is significantly improves word segmentation. Experiments using Spanish documents from the Marriages Database of the Barcelona Cathedral show that this approach reduces the error rate by more than 20% |
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978-1-4673-2262-1 |
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ICFHR |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ FLF2012 |
Serial |
2200 |
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| Author |
David Fernandez; Pau Riba; Alicia Fornes; Josep Llados |
| Title |
On the Influence of Key Point Encoding for Handwritten Word Spotting |
Type |
Conference Article |
| Year |
2014 |
Publication |
14th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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Pages |
476 - 481 |
| Keywords |
Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis |
| Abstract |
In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries. |
| Address |
Creete Island; Grecia; September 2014 |
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2167-6445 |
ISBN |
978-1-4799-4335-7 |
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ICFHR |
| Notes |
DAG; 600.056; 600.061; 602.006; 600.077 |
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no |
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Admin @ si @ FRF2014 |
Serial |
2460 |
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| Author |
Pau Riba; Jon Almazan; Alicia Fornes; David Fernandez; Ernest Valveny; Josep Llados |
| Title |
e-Crowds: a mobile platform for browsing and searching in historical demographyrelated manuscripts |
Type |
Conference Article |
| Year |
2014 |
Publication |
14th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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Pages |
228 - 233 |
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| Abstract |
This paper presents a prototype system running on portable devices for browsing and word searching through historical handwritten document collections. The platform adapts the paradigm of eBook reading, where the narrative is not necessarily sequential, but centered on the user actions. The novelty is to replace digitally born books by digitized historical manuscripts of marriage licenses, so document analysis tasks are required in the browser. With an active reading paradigm, the user can cast queries of people names, so he/she can implicitly follow genealogical links. In addition, the system allows combined searches: the user can refine a search by adding more words to search. As a second contribution, the retrieval functionality involves as a core technology a word spotting module with an unified approach, which allows combined query searches, and also two input modalities: query-by-example, and query-by-string. |
| Address |
Creete Island; Grecia; September 2014 |
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2167-6445 |
ISBN |
978-1-4799-4335-7 |
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ICFHR |
| Notes |
DAG; 600.056; 600.045; 600.061; 602.006; 600.077 |
Approved |
no |
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Admin @ si @ RAF2014 |
Serial |
2463 |
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| Author |
Arnau Baro; Pau Riba; Alicia Fornes |
| Title |
Towards the recognition of compound music notes in handwritten music scores |
Type |
Conference Article |
| Year |
2016 |
Publication |
15th international conference on Frontiers in Handwriting Recognition |
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The recognition of handwritten music scores still remains an open problem. The existing approaches can only deal with very simple handwritten scores mainly because of the variability in the handwriting style and the variability in the composition of groups of music notes (i.e. compound music notes). In this work we focus on this second problem and propose a method based on perceptual grouping for the recognition of compound music notes. Our method has been tested using several handwritten music scores of the CVC-MUSCIMA database and compared with a commercial Optical Music Recognition (OMR) software. Given that our method is learning-free, the obtained results are promising. |
| Address |
Shenzhen; China; October 2016 |
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2167-6445 |
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ICFHR |
| Notes |
DAG; 600.097 |
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no |
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Admin @ si @ BRF2016 |
Serial |
2903 |
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