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Author |
Cristhian Aguilera; Xavier Soria; Angel Sappa; Ricardo Toledo |
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Title |
RGBN Multispectral Images: a Novel Color Restoration Approach |
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Conference Article |
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2017 |
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15th International Conference on Practical Applications of Agents and Multi-Agent System |
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Multispectral Imaging; Free Sensor Model; Neural Network |
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This paper describes a color restoration technique used to remove NIR information from single sensor cameras where color and near-infrared images are simultaneously acquired|referred to in the literature as RGBN images. The proposed approach is based on a neural network architecture that learns the NIR information contained in the RGBN images. The proposed approach is evaluated on real images obtained by using a pair of RGBN cameras. Additionally, qualitative comparisons with a nave color correction technique based on mean square
error minimization are provided. |
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Porto; Portugal; June 2017 |
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PAAMS |
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ADAS; MSIAU; 600.118; 600.122 |
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Admin @ si @ ASS2017 |
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2918 |
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Pau Rodriguez; Jordi Gonzalez; Jordi Cucurull; Josep M. Gonfaus; Xavier Roca |
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Title |
Regularizing CNNs with Locally Constrained Decorrelations |
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2017 |
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5th International Conference on Learning Representations |
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Toulon; France; April 2017 |
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ICLR |
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ISE; 602.143; 600.119; 600.098 |
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Admin @ si @ RGC2017 |
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2927 |
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Author |
Umut Guclu; Yagmur Gucluturk; Meysam Madadi; Sergio Escalera; Xavier Baro; Jordi Gonzalez; Rob van Lier; Marcel A. J. van Gerven |
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Title |
End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks |
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Miscellaneous |
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2017 |
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Arxiv |
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arXiv:1703.03305
Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation. Here, we tackle this problem by leveraging the respective strengths of these advances. That is, we formulate a conditional random field over a four-connected graph as end-to-end trainable convolutional and recurrent networks, and estimate them via an adversarial process. Importantly, our model learns not only unary potentials but also pairwise
potentials, while aggregating multi-scale contexts and controlling higher-order inconsistencies.
We evaluate our model on two standard benchmark datasets for semantic face segmentation, achieving state-of-the-art results on both of them. |
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HuPBA; ISE; 600.098; 600.119 |
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Admin @ si @ GGM2017 |
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2932 |
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Author |
H. Martin Kjer; Jens Fagertun; Sergio Vera; Debora Gil |
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Title |
Medial structure generation for registration of anatomical structures |
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Book Chapter |
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2017 |
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Skeletonization, Theory, Methods and Applications |
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11 |
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IAM; 600.096; 600.075; 600.145 |
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Admin @ si @ MFV2017a |
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2935 |
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Author |
Mireia Sole; Joan Blanco; Debora Gil; Oliver Valero; G. Fonseka; M. Lawrie; Francesca Vidal; Zaida Sarrate |
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Title |
Chromosome Territories in Mice Spermatogenesis: A new three-dimensional methodology of study |
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Conference Article |
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2017 |
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11th European CytoGenesis Conference |
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Florencia; Italia; July 2017 |
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ECA |
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IAM; 600.096; 600.145 |
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Admin @ si @ SBG2017a |
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2936 |
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Author |
Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez |
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Title |
Computer Vision in Vehicle Technology: Land, Sea & Air |
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Book Whole |
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2017 |
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161-163 |
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Summary This chapter examines different vision-based commercial solutions for real-live problems related to vehicles. It is worth mentioning the recent astonishing performance of deep convolutional neural networks (DCNNs) in difficult visual tasks such as image classification, object recognition/localization/detection, and semantic segmentation. In fact,
different DCNN architectures are already being explored for low-level tasks such as optical flow and disparity computation, and higher level ones such as place recognition. |
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John Wiley & Sons, Ltd |
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978-1-118-86807-2 |
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ADAS; 600.118 |
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no |
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Admin @ si @ LIP2017a |
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2937 |
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Author |
Carles Sanchez; Debora Gil; T. Gache; N. Koufos; Marta Diez-Ferrer; Antoni Rosell |
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Title |
SENSA: a System for Endoscopic Stenosis Assessment |
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Conference Article |
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2016 |
Publication |
28th Conference of the international Society for Medical Innovation and Technology |
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Documenting the severity of a static or dynamic Central Airway Obstruction (CAO) is crucial to establish proper diagnosis and treatment, predict possible treatment effects and better follow-up the patients. The subjective visual evaluation of a stenosis during video-bronchoscopy still remains the most common way to assess a CAO in spite of a consensus among experts for a need to standardize all calculations [1].
The Computer Vision Center in cooperation with the «Hospital de Bellvitge», has developed a System for Endoscopic Stenosis Assessment (SENSA), which computes CAO directly by analyzing standard bronchoscopic data without the need of using other imaging tecnologies. |
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Rotterdam; The Netherlands; October 2016 |
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SMIT |
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IAM; |
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Admin @ si @ SGG2016 |
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2942 |
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Author |
Carles Sanchez; Antonio Esteban Lansaque; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil |
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Title |
Towards a Videobronchoscopy Localization System from Airway Centre Tracking |
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Conference Article |
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2017 |
Publication |
12th International Conference on Computer Vision Theory and Applications |
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352-359 |
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Video-bronchoscopy; Lung cancer diagnosis; Airway lumen detection; Region tracking; Guided bronchoscopy navigation |
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Bronchoscopists use fluoroscopy to guide flexible bronchoscopy to the lesion to be biopsied without any kind of incision. Being fluoroscopy an imaging technique based on X-rays, the risk of developmental problems and cancer is increased in those subjects exposed to its application, so minimizing radiation is crucial. Alternative guiding systems such as electromagnetic navigation require specific equipment, increase the cost of the clinical procedure and still require fluoroscopy. In this paper we propose an image based guiding system based on the extraction of airway centres from intra-operative videos. Such anatomical landmarks are matched to the airway centreline extracted from a pre-planned CT to indicate the best path to the nodule. We present a
feasibility study of our navigation system using simulated bronchoscopic videos and a multi-expert validation of landmarks extraction in 3 intra-operative ultrathin explorations. |
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Porto; Portugal; February 2017 |
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VISAPP |
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IAM; 600.096; 600.075; 600.145 |
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Admin @ si @ SEB2017 |
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2943 |
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Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Maroua Hammami; Gloria Fernandez Esparrach; Xavier Dray; Olivier Romain; F. Javier Sanchez; Aymeric Histace |
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Real-Time Polyp Detection in Colonoscopy Videos: A Preliminary Study For Adapting Still Frame-based Methodology To Video Sequences Analysis |
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2017 |
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31st International Congress and Exhibition on Computer Assisted Radiology and Surgery |
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Barcelona; Spain; June 2017 |
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CARS |
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MV; no menciona |
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Admin @ si @ ABS2017 |
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2947 |
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Lasse Martensson; Anders Hast; Alicia Fornes |
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Title |
Word Spotting as a Tool for Scribal Attribution |
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2017 |
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2nd Conference of the association of Digital Humanities in the Nordic Countries |
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87-89 |
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Gothenburg; Suecia; March 2017 |
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978-91-88348-83-8 |
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DHN |
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DAG; 600.097; 600.121 |
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Admin @ si @ MHF2017 |
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2954 |
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Author |
Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades |
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Title |
Spotting Symbol over Graphical Documents Via Sparsity in Visual Vocabulary |
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2016 |
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Recent Trends in Image Processing and Pattern Recognition |
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709 |
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RTIP2R |
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DAG |
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Admin @ si @ HTR2016 |
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2956 |
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Author |
Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate |
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Title |
Is there a pattern of Chromosome territoriality along mice spermatogenesis? |
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Conference Article |
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2017 |
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3rd Spanish MeioNet Meeting Abstract Book |
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55-56 |
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Miraflores de la Sierra; Madrid; June 2017 |
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MEIONET |
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IAM; 600.096; 600.145 |
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Admin @ si @ |
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2958 |
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Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate |
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Title |
Unraveling the enigmas of chromosome territoriality during spermatogenesis |
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Conference Article |
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2017 |
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IX Jornada del Departament de Biologia Cel•lular, Fisiologia i Immunologia |
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UAB; Barcelona; June 2017 |
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IAM; 600.145 |
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Admin @ si @ SBG2017b |
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2959 |
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Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Francesca Vidal; Zaida Sarrate |
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Title |
Noves perspectives en l estudi de la territorialitat cromosomica de cel·lules germinals masculines: estudis tridimensionals |
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2017 |
Publication |
Biologia de la Reproduccio |
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JBR |
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15 |
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73-78 |
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In somatic cells, chromosomes occupy specific nuclear regions called chromosome territories which are involved in the
maintenance and regulation of the genome. Preliminary data in male germ cells also suggest the importance of chromosome
territoriality in cell functionality. Nevertheless, the specific characteristics of testicular tissue (presence of different
cell types with different morphological characteristics, in different stages of development and with different ploidy)
makes difficult to achieve conclusive results. In this study we have developed a methodology to approach the threedimensional
study of all chromosome territories in male germ cells from C57BL/6J mice (Mus musculus). The method
includes the following steps: i) Optimized cell fixation to obtain an optimal preservation of the three-dimensionality cell
morphology, ii) Chromosome identification by FISH (Chromoprobe Multiprobe® OctoChrome™ Murine System; Cytocell)
and confocal microscopy (TCS-SP5, Leica Microsystems), iii) Cell type identification by immunofluorescence
iv) Image analysis using Matlab scripts, v) Numerical data extraction related to chromosome features, chromosome
radial position and chromosome relative position. This methodology allows the unequivocally identification and the
analysis of the chromosome territories of all spermatogenic stages. Results will provide information about the features
that determine chromosomal position, preferred associations between chromosomes, and the relationship between chromosome
positioning and genome regulation. |
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978-84-697-3767-5 |
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IAM; 600.096; 600.145 |
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Admin @ si @ SBG2017c |
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2961 |
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Permanent link to this record |
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Author |
Xinhang Song; Luis Herranz; Shuqiang Jiang |
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Title |
Depth CNNs for RGB-D Scene Recognition: Learning from Scratch Better than Transferring from RGB-CNNs |
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Conference Article |
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2017 |
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31st AAAI Conference on Artificial Intelligence |
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RGB-D scene recognition; weakly supervised; fine tune; CNN |
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Abstract |
Scene recognition with RGB images has been extensively studied and has reached very remarkable recognition levels, thanks to convolutional neural networks (CNN) and large scene datasets. In contrast, current RGB-D scene data is much more limited, so often leverages RGB large datasets, by transferring pretrained RGB CNN models and fine-tuning with the target RGB-D dataset. However, we show that this approach has the limitation of hardly reaching bottom layers, which is key to learn modality-specific features. In contrast, we focus on the bottom layers, and propose an alternative strategy to learn depth features combining local weakly supervised training from patches followed by global fine tuning with images. This strategy is capable of learning very discriminative depth-specific features with limited depth images, without resorting to Places-CNN. In addition we propose a modified CNN architecture to further match the complexity of the model and the amount of data available. For RGB-D scene recognition, depth and RGB features are combined by projecting them in a common space and further leaning a multilayer classifier, which is jointly optimized in an end-to-end network. Our framework achieves state-of-the-art accuracy on NYU2 and SUN RGB-D in both depth only and combined RGB-D data. |
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San Francisco CA; February 2017 |
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AAAI |
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LAMP; 600.120 |
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no |
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Admin @ si @ SHJ2017 |
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2967 |
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