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Author | Katerine Diaz; Jesus Martinez del Rincon; Aura Hernandez-Sabate | ||||
Title | Decremental generalized discriminative common vectors applied to images classification | Type | Journal Article | ||
Year | 2017 | Publication | Knowledge-Based Systems | Abbreviated Journal | KBS |
Volume | 131 | Issue | Pages | 46-57 | |
Keywords | Decremental learning; Generalized Discriminative Common Vectors; Feature extraction; Linear subspace methods; Classification | ||||
Abstract | In this paper, a novel decremental subspace-based learning method called Decremental Generalized Discriminative Common Vectors method (DGDCV) is presented. The method makes use of the concept of decremental learning, which we introduce in the field of supervised feature extraction and classification. By efficiently removing unnecessary data and/or classes for a knowledge base, our methodology is able to update the model without recalculating the full projection or accessing to the previously processed training data, while retaining the previously acquired knowledge. The proposed method has been validated in 6 standard face recognition datasets, showing a considerable computational gain without compromising the accuracy of the model. | ||||
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Notes | ADAS; 600.118; 600.121 | Approved | no | ||
Call Number | Admin @ si @ DMH2017a | Serial | 3003 | ||
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Author | Sergio Escalera; Vassilis Athitsos; Isabelle Guyon | ||||
Title | Challenges in Multi-modal Gesture Recognition | Type | Book Chapter | ||
Year | 2017 | Publication | Abbreviated Journal | ||
Volume | Issue | Pages | 1-60 | ||
Keywords | Gesture recognition; Time series analysis; Multimodal data analysis; Computer vision; Pattern recognition; Wearable sensors; Infrared cameras; Kinect TMTM | ||||
Abstract | This paper surveys the state of the art on multimodal gesture recognition and introduces the JMLR special topic on gesture recognition 2011–2015. We began right at the start of the Kinect TMTM revolution when inexpensive infrared cameras providing image depth recordings became available. We published papers using this technology and other more conventional methods, including regular video cameras, to record data, thus providing a good overview of uses of machine learning and computer vision using multimodal data in this area of application. Notably, we organized a series of challenges and made available several datasets we recorded for that purpose, including tens of thousands of videos, which are available to conduct further research. We also overview recent state of the art works on gesture recognition based on a proposed taxonomy for gesture recognition, discussing challenges and future lines of research. | ||||
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Notes | HuPBA; no proj | Approved | no | ||
Call Number | Admin @ si @ EAG2017 | Serial | 3008 | ||
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Author | Jordi Esquirol; Cristina Palmero; Vanessa Bayo; Miquel Angel Cos; Sergio Escalera; David Sanchez; Maider Sanchez; Noelia Serrano; Mireia Relats | ||||
Title | Automatic RBG-depth-pressure anthropometric analysis and individualised sleep solution prescription | Type | Journal | ||
Year | 2017 | Publication | Journal of Medical Engineering & Technology | Abbreviated Journal | JMET |
Volume | 41 | Issue | 6 | Pages | 486-497 |
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Abstract | INTRODUCTION:
Sleep surfaces must adapt to individual somatotypic features to maintain a comfortable, convenient and healthy sleep, preventing diseases and injuries. Individually determining the most adequate rest surface can often be a complex and subjective question. OBJECTIVES: To design and validate an automatic multimodal somatotype determination model to automatically recommend an individually designed mattress-topper-pillow combination. METHODS: Design and validation of an automated prescription model for an individualised sleep system is performed through a single-image 2 D-3 D analysis and body pressure distribution, to objectively determine optimal individual sleep surfaces combining five different mattress densities, three different toppers and three cervical pillows. RESULTS: A final study (n = 151) and re-analysis (n = 117) defined and validated the model, showing high correlations between calculated and real data (>85% in height and body circumferences, 89.9% in weight, 80.4% in body mass index and more than 70% in morphotype categorisation). CONCLUSIONS: Somatotype determination model can accurately prescribe an individualised sleep solution. This can be useful for healthy people and for health centres that need to adapt sleep surfaces to people with special needs. Next steps will increase model's accuracy and analise, if this prescribed individualised sleep solution can improve sleep quantity and quality; additionally, future studies will adapt the model to mattresses with technological improvements, tailor-made production and will define interfaces for people with special needs. |
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Notes | HUPBA; no menciona | Approved | no | ||
Call Number | Admin @ si @ EPB2017 | Serial | 3010 | ||
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Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera; Huamin Ren; Thomas B. Moeslund; Elham Etemad | ||||
Title | Locality Regularized Group Sparse Coding for Action Recognition | Type | Journal Article | ||
Year | 2017 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 158 | Issue | Pages | 106-114 | |
Keywords | Bag of words; Feature encoding; Locality constrained coding; Group sparse coding; Alternating direction method of multipliers; Action recognition | ||||
Abstract | Bag of visual words (BoVW) models are widely utilized in image/ video representation and recognition. The cornerstone of these models is the encoding stage, in which local features are decomposed over a codebook in order to obtain a representation of features. In this paper, we propose a new encoding algorithm by jointly encoding the set of local descriptors of each sample and considering the locality structure of descriptors. The proposed method takes advantages of locality coding such as its stability and robustness to noise in descriptors, as well as the strengths of the group coding strategy by taking into account the potential relation among descriptors of a sample. To efficiently implement our proposed method, we consider the Alternating Direction Method of Multipliers (ADMM) framework, which results in quadratic complexity in the problem size. The method is employed for a challenging classification problem: action recognition by depth cameras. Experimental results demonstrate the outperformance of our methodology compared to the state-of-the-art on the considered datasets. | ||||
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Notes | HuPBA; no proj | Approved | no | ||
Call Number | Admin @ si @ BGE2017 | Serial | 3014 | ||
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Author | Laura Igual; Santiago Segui | ||||
Title | Introduction to Data Science – A Python Approach to Concepts, Techniques and Applications. Undergraduate Topics in Computer Science | Type | Book Whole | ||
Year | 2017 | Publication | Abbreviated Journal | ||
Volume | Issue | Pages | 1-215 | ||
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Publisher | 978-3-319-50016-4 | Place of Publication | Editor | ||
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ISSN | ISBN | 978-3-319-50016-4 | Medium | ||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ IgS2017 | Serial | 3027 | ||
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Author | Mireia Forns-Nadal; Federico Sem; Anna Mane; Laura Igual; Dani Guinart; Oscar Vilarroya | ||||
Title | Increased Nucleus Accumbens Volume in First-Episode Psychosis | Type | Journal Article | ||
Year | 2017 | Publication | Psychiatry Research-Neuroimaging | Abbreviated Journal | PRN |
Volume | 263 | Issue | Pages | 57-60 | |
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Abstract | Nucleus accumbens has been reported as a key structure in the neurobiology of schizophrenia. Studies analyzing structural abnormalities have shown conflicting results, possibly related to confounding factors. We investigated the nucleus accumbens volume using manual delimitation in first-episode psychosis (FEP) controlling for age, cannabis use and medication. Thirty-one FEP subjects who were naive or minimally exposed to antipsychotics and a control group were MRI scanned and clinically assessed from baseline to 6 months of follow-up. FEP showed increased relative and total accumbens volumes. Clinical correlations with negative symptoms, duration of untreated psychosis and cannabis use were not significant. | ||||
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Notes | MILAB; no menciona | Approved | no | ||
Call Number | Admin @ si @ FSM2017 | Serial | 3028 | ||
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Author | Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate | ||||
Title | Análisis 3d de la territorialidad cromosómica en células espermatogénicas: explorando la infertilidad desde un nuevo prisma | Type | Journal | ||
Year | 2017 | Publication | Revista Asociación para el Estudio de la Biología de la Reproducción | Abbreviated Journal | ASEBIR |
Volume | 22 | Issue | 2 | Pages | 105 |
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Notes | IAM; 600.096; 600.145 | Approved | no | ||
Call Number | Admin @ si @ SBG2017d | Serial | 3042 | ||
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Author | Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes; Sounak Dey | ||||
Title | Improving Information Retrieval in Multiwriter Scenario by Exploiting the Similarity Graph of Document Terms | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 475-480 | ||
Keywords | document terms; information retrieval; affinity graph; graph of document terms; multiwriter; graph diffusion | ||||
Abstract | Information Retrieval (IR) is the activity of obtaining information resources relevant to a questioned information. It usually retrieves a set of objects ranked according to the relevancy to the needed fact. In document analysis, information retrieval receives a lot of attention in terms of symbol and word spotting. However, through decades the community mostly focused either on printed or on single writer scenario, where the
state-of-the-art results have achieved reasonable performance on the available datasets. Nevertheless, the existing algorithms do not perform accordingly on multiwriter scenario. A graph representing relations between a set of objects is a structure where each node delineates an individual element and the similarity between them is represented as a weight on the connecting edge. In this paper, we explore different analytics of graphs constructed from words or graphical symbols, such as diffusion, shortest path, etc. to improve the performance of information retrieval methods in multiwriter scenario |
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.097; 601.302; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RDL2017a | Serial | 3053 | ||
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Author | Anjan Dutta; Pau Riba; Josep Llados; Alicia Fornes | ||||
Title | Pyramidal Stochastic Graphlet Embedding for Document Pattern Classification | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 33-38 | ||
Keywords | graph embedding; hierarchical graph representation; graph clustering; stochastic graphlet embedding; graph classification | ||||
Abstract | Document pattern classification methods using graphs have received a lot of attention because of its robust representation paradigm and rich theoretical background. However, the way of preserving and the process for delineating documents with graphs introduce noise in the rendition of underlying data, which creates instability in the graph representation. To deal with such unreliability in representation, in this paper, we propose Pyramidal Stochastic Graphlet Embedding (PSGE).
Given a graph representing a document pattern, our method first computes a graph pyramid by successively reducing the base graph. Once the graph pyramid is computed, we apply Stochastic Graphlet Embedding (SGE) for each level of the pyramid and combine their embedded representation to obtain a global delineation of the original graph. The consideration of pyramid of graphs rather than just a base graph extends the representational power of the graph embedding, which reduces the instability caused due to noise and distortion. When plugged with support vector machine, our proposed PSGE has outperformed the state-of-the-art results in recognition of handwritten words as well as graphical symbols |
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.097; 601.302; 600.121 | Approved | no | ||
Call Number | Admin @ si @ DRL2017 | Serial | 3054 | ||
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Author | Juan Ignacio Toledo; Sounak Dey; Alicia Fornes; Josep Llados | ||||
Title | Handwriting Recognition by Attribute embedding and Recurrent Neural Networks | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1038-1043 | ||
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Abstract | Handwriting recognition consists in obtaining the transcription of a text image. Recent word spotting methods based on attribute embedding have shown good performance when recognizing words. However, they are holistic methods in the sense that they recognize the word as a whole (i.e. they find the closest word in the lexicon to the word image). Consequently,
these kinds of approaches are not able to deal with out of vocabulary words, which are common in historical manuscripts. Also, they cannot be extended to recognize text lines. In order to address these issues, in this paper we propose a handwriting recognition method that adapts the attribute embedding to sequence learning. Concretely, the method learns the attribute embedding of patches of word images with a convolutional neural network. Then, these embeddings are presented as a sequence to a recurrent neural network that produces the transcription. We obtain promising results even without the use of any kind of dictionary or language model |
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.097; 601.225; 600.121 | Approved | no | ||
Call Number | Admin @ si @ TDF2017 | Serial | 3055 | ||
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Author | Arnau Baro; Pau Riba; Jorge Calvo-Zaragoza; Alicia Fornes | ||||
Title | Optical Music Recognition by Recurrent Neural Networks | Type | Conference Article | ||
Year | 2017 | Publication | 14th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 25-26 | ||
Keywords | Optical Music Recognition; Recurrent Neural Network; Long Short-Term Memory | ||||
Abstract | Optical Music Recognition is the task of transcribing a music score into a machine readable format. Many music scores are written in a single staff, and therefore, they could be treated as a sequence. Therefore, this work explores the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for reading the music score sequentially, where the LSTM helps in keeping the context. For training, we have used a synthetic dataset of more than 40000 images, labeled at primitive level | ||||
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.097; 601.302; 600.121 | Approved | no | ||
Call Number | Admin @ si @ BRC2017 | Serial | 3056 | ||
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Author | Sounak Dey; Anjan Dutta; Josep Llados; Alicia Fornes; Umapada Pal | ||||
Title | Shallow Neural Network Model for Hand-drawn Symbol Recognition in Multi-Writer Scenario | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 31-32 | ||
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Abstract | One of the main challenges in hand drawn symbol recognition is the variability among symbols because of the different writer styles. In this paper, we present and discuss some results recognizing hand-drawn symbols with a shallow neural network. A neural network model inspired from the LeNet architecture has been used to achieve state-of-the-art results with
very less training data, which is very unlikely to the data hungry deep neural network. From the results, it has become evident that the neural network architectures can efficiently describe and recognize hand drawn symbols from different writers and can model the inter author aberration |
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ DDL2017 | Serial | 3057 | ||
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Author | Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes | ||||
Title | Graph-based deep learning for graphics classification | Type | Conference Article | ||
Year | 2017 | Publication | 14th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 29-30 | ||
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Abstract | Graph-based representations are a common way to deal with graphics recognition problems. However, previous works were mainly focused on developing learning-free techniques. The success of deep learning frameworks have proved that learning is a powerful tool to solve many problems, however it is not straightforward to extend these methodologies to non euclidean data such as graphs. On the other hand, graphs are a good representational structure for graphical entities. In this work, we present some deep learning techniques that have been proposed in the literature for graph-based representations and
we show how they can be used in graphics recognition problems |
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.097; 601.302; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RDL2017b | Serial | 3058 | ||
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Author | Adria Rico; Alicia Fornes | ||||
Title | Camera-based Optical Music Recognition using a Convolutional Neural Network | Type | Conference Article | ||
Year | 2017 | Publication | 12th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 27-28 | ||
Keywords | optical music recognition; document analysis; convolutional neural network; deep learning | ||||
Abstract | Optical Music Recognition (OMR) consists in recognizing images of music scores. Contrary to expectation, the current OMR systems usually fail when recognizing images of scores captured by digital cameras and smartphones. In this work, we propose a camera-based OMR system based on Convolutional Neural Networks, showing promising preliminary results | ||||
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Area | Expedition | Conference | GREC | ||
Notes | DAG;600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RiF2017 | Serial | 3059 | ||
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Author | Oriol Vicente; Alicia Fornes; Ramon Valdes | ||||
Title | La Xarxa d Humanitats Digitals de la UABCie: una estructura inteligente para la investigación y la transferencia en Humanidades | Type | Conference Article | ||
Year | 2017 | Publication | 3rd Congreso Internacional de Humanidades Digitales Hispánicas. Sociedad Internacional | Abbreviated Journal | |
Volume | Issue | Pages | 281-383 | ||
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ISSN | ISBN | 978-84-697-5692-8 | Medium | ||
Area | Expedition | Conference | HDH | ||
Notes | DAG; 600.121 | Approved | no | ||
Call Number | Admin @ si @ VFV2017 | Serial | 3060 | ||
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