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Consistent model reduction of polymer chains in solution in dissipative particle dynamics: Model description

Nicolas Moreno, Suzana P. Nunes, Victor M. Calo
2015 Computer Physics Communications  
Based on geometrical considerations we map fine-grained models to a reference state through a consistent scaling of the system, where short length and fast time scales are disregarded while the properties  ...  Following this coarse graining process we consistently represent high molecular weight DPD chains (i.e., >200 beads per chain) with a significant reduction in the number of particles required (i.e., >  ...  Since our goal is to perform model reduction on DPD while preserving relevant structural properties close to those of the original fine-scale simulation, the scaling of the mass (23) and length (24) units  ... 
doi:10.1016/j.cpc.2015.06.012 fatcat:56ybfwgrljcklou45scmrlypje

The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification [article]

Tianjun Xiao, Yichong Xu, Kuiyuan Yang, Jiaxing Zhang, Yuxin Peng, Zheng Zhang
2014 arXiv   pre-print
Fine-grained classification is challenging because categories can only be discriminated by subtle and local differences.  ...  In this paper, we propose to apply visual attention to fine-grained classification task using deep neural network.  ...  This leads to better CNN feature for fine-grained classification, as the network are driven by domain-relevant patches that are also rich with shift/scale variances.  ... 
arXiv:1411.6447v1 fatcat:33okswdifzfldmj6pqwn6f4vxu

Restrictions in Model Reduction for Polymer Chain Models in Dissipative Particle Dynamics

Nicolas Moreno, Suzana Nunes, Victor M. Calo
2014 Procedia Computer Science  
., density ρ, pressure p, temperature T , radial distribution function g(r)) but preserving also the characteristic shape and length scale of the polymer chain model is necessary.  ...  DPD-model-reduction methodology for linear polymers recently proposed; and demonstrate why the applicability of this methodology is limited upto certain maximum polymer length, and not suitable for solvent coarse graining  ...  The upper limits in chain lengths and coarse grain level were identified by [18] based on the construction of the phase diagram for fine-and coarse-grained systems.  ... 
doi:10.1016/j.procs.2014.05.065 fatcat:mfklchanwjbyncbuxyfczsway4

Text-based inference of moral sentiment change [article]

Jing Yi Xie, Renato Ferreira Pinto Jr., Graeme Hirst, Yang Xu
2020 arXiv   pre-print
, moral polarity, and fine-grained moral dimensions.  ...  We apply this methodology to visualizing moral time courses of individual concepts and analyzing the relations between psycholinguistic variables and rates of moral sentiment change at scale.  ...  We would also like to thank Ben Prystawski for his feedback on the manuscript.  ... 
arXiv:2001.07209v1 fatcat:wunuojvhbja27hnk2ba2jvbnzi

Learning Fine-Grained Image Similarity with Deep Ranking

Jiang Wang, Yang Song, Thomas Leung, Chuck Rosenberg, Jingbin Wang, James Philbin, Bo Chen, Ying Wu
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
Learning fine-grained image similarity is a challenging task. It needs to capture between-class and within-class image differences.  ...  Extensive experiments show that the proposed algorithm outperforms models based on hand-crafted visual features and deep classification models.  ...  ., fine-grained image similarity.  ... 
doi:10.1109/cvpr.2014.180 dblp:conf/cvpr/WangSLRWPCW14 fatcat:mywmmpbizfelje2fbmmehqiyn4

The application of two-level attention models in deep convolutional neural network for fine-grained image classification

Tianjun Xiao, Yichong Xu, Kuiyuan Yang, Jiaxing Zhang, Yuxin Peng, Zheng Zhang
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Fine-grained classification is challenging because categories can only be discriminated by subtle and local differences.  ...  Most fine-grained classification systems follow the pipeline of finding foreground object or object parts (where) to extract discriminative features (what).  ...  This leads to better CNN feature for fine-grained classification, as the network is driven by domain-relevant patches that are also rich with shift/scale variances.  ... 
doi:10.1109/cvpr.2015.7298685 dblp:conf/cvpr/XiaoXYZPZ15 fatcat:o7bnt3iz5nc5lh5k5gl7okxjrq

Learning Fine-grained Image Similarity with Deep Ranking [article]

Jiang Wang, Yang song, Thomas Leung, Chuck Rosenberg, Jinbin Wang, James Philbin, Bo Chen, Ying Wu
2014 arXiv   pre-print
Learning fine-grained image similarity is a challenging task. It needs to capture between-class and within-class image differences.  ...  Extensive experiments show that the proposed algorithm outperforms models based on hand-crafted visual features and deep classification models.  ...  ., fine-grained image similarity.  ... 
arXiv:1404.4661v1 fatcat:uezz2kslnfajjmqziqj3t77uj4

Fine-grained Classification via Categorical Memory Networks [article]

Weijian Deng, Joshua Marsh, Stephen Gould, Liang Zheng
2020 arXiv   pre-print
Motivated by the desire to exploit patterns shared across classes, we present a simple yet effective class-specific memory module for fine-grained feature learning.  ...  Our memory module significantly improves accuracy over baseline CNNs, achieving competitive accuracy with state-of-the-art methods on four benchmarks, including CUB-200-2011, Stanford Cars, FGVC Aircraft  ...  In our case, each prototype represents one fine-grained class.  ... 
arXiv:2012.06793v1 fatcat:csxxhxynuzdnbmnxhznczbiiqy

Incorporating fine‐scale environmental heterogeneity into broad‐extent models

Laura J. Graham, Rebecca Spake, Simon Gillings, Kevin Watts, Felix Eigenbrod, Nick Isaac
2019 Methods in Ecology and Evolution  
on fine-grain spatial structure in environmental heterogeneity for use with coarse-grain ecological datasets.  ...  ) at the process-relevant scale (scale-of-effect); and (c) aggregate the moving window calculations to the coarsest resolution (response grain).  ...  at the most relevant scale in combination with other, coarse-grain predictor variables.  ... 
doi:10.1111/2041-210x.13177 pmid:31244985 pmcid:PMC6582547 fatcat:va3wkvq2djbajhmw5fnixikecy

Large Scale Visual Food Recognition [article]

Weiqing Min and Zhiling Wang and Yuxin Liu and Mengjiang Luo and Liping Kang and Xiaoming Wei and Xiaolin Wei and Shuqiang Jiang
2021 arXiv   pre-print
We also hope Food2K can serve as a large scale fine-grained visual recognition benchmark.  ...  Food2K can be further explored to benefit more food-relevant tasks including emerging and more complex ones (e.g., nutritional understanding of food), and the trained models on Food2K can be expected as  ...  In addition, Food2K can be expected to be one large-scale fine-grained visual recognition benchmark to enable the development of finegrained visual recognition.  ... 
arXiv:2103.16107v2 fatcat:ewfhhmi7gbfqrjzvmfgqdnju5y

Text-based inference of moral sentiment change

Jing Yi Xie, Renato Ferreira Pinto Junior, Graeme Hirst, Yang Xu
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
, moral polarity, and fine-grained moral dimensions.  ...  We apply this methodology to visualizing moral time courses of individual concepts and analyzing the relations between psycholinguistic variables and rates of moral sentiment change at scale.  ...  We would also like to thank Ben Prystawski for his feedback on the manuscript.  ... 
doi:10.18653/v1/d19-1472 dblp:conf/emnlp/XieJHX19 fatcat:gw2ratcv3fgffcybni4qnrrkku

Generalized orderless pooling performs implicit salient matching [article]

Marcel Simon, Yang Gao, Trevor Darrell, Joachim Denzler, Erik Rodner
2017 arXiv   pre-print
For example, we can show that the higher capacity VGG16 model focuses much more on the bird's head than, e.g., the lower-capacity VGG-M model when recognizing fine-grained bird categories.  ...  In the field of fine-grained recognition, however, recent global representations like bilinear pooling offer improved performance.  ...  Discussion Fine-grained tasks are about focusing on a few relevant areas Our in-depth analysis revealed that a high accuracy for fine-grained recognition can be achieved when only a few relevant areas  ... 
arXiv:1705.00487v3 fatcat:imvqfglspjdijgfpi6p2qk63re

The ecology of scale

Max Rietkerk, Johan van de Koppel, Lalit Kumar, Herbert H.T. Langevelde, Prins
2002 Ecological Modelling  
To detect scale-dependent processes and patterns one depends on observation sets or model calculations of fine grain and large extent.  ...  Second, thinking cross-scale means that one has to acknowledge scale transfer. Third, one has thus to explicitly define the grain and extent of the investigations.  ... 
doi:10.1016/s0304-3800(01)00510-5 fatcat:upowkqqfgvcrfbuejsjn72g6sa

Parallel Streaming Signature EM-tree

Christopher Michael De Vries, Lance De Vine, Shlomo Geva, Richi Nayak
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15  
These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation.  ...  It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes.  ...  Fine grained clustering is not achievable through aggressive subsampling in web-scale collections.  ... 
doi:10.1145/2736277.2741111 dblp:conf/www/VriesVGN15 fatcat:htqbtmzvebbaxfng5benjvjpse

Coarse-graining dynamical triangulations: a new scheme

Joe Henson
2009 Classical and quantum gravity  
In order for a coarse-graining process to be useful, it should preserve the properties of the original dynamical triangulation that are relevant when probing at large scales.  ...  The procedure provides a meaning for the relevant value of observables when "probing at large scales", e.g. the average scalar curvature.  ...  As suggested by the brief comments above, it is absolutely crucial that, on large scales, this coarse-graining corresponds to the original fine-grained version on large scales.  ... 
doi:10.1088/0264-9381/26/17/175019 fatcat:fhhcq534crdq5hpngz7xkedxo4
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