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Author Aura Hernandez-Sabate; Lluis Albarracin; F. Javier Sanchez edit  doi
openurl 
  Title Graph-Based Problem Explorer: A Software Tool to Support Algorithm Design Learning While Solving the Salesperson Problem Type Journal
  Year 2020 Publication Mathematics Abbreviated Journal MATH  
  Volume (down) 20 Issue 8(9) Pages 1595  
  Keywords STEM education; Project-based learning; Coding; software tool  
  Abstract In this article, we present a sequence of activities in the form of a project in order to promote
learning on design and analysis of algorithms. The project is based on the resolution of a real problem, the salesperson problem, and it is theoretically grounded on the fundamentals of mathematical modelling. In order to support the students’ work, a multimedia tool, called Graph-based Problem Explorer (GbPExplorer), has been designed and refined to promote the development of computer literacy in engineering and science university students. This tool incorporates several modules to allow coding different algorithmic techniques solving the salesman problem. Based on an educational design research along five years, we observe that working with GbPExplorer during the project provides students with the possibility of representing the situation to be studied in the form of graphs and analyze them from a computational point of view.
 
  Address September 2020  
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  Notes IAM; ISE Approved no  
  Call Number Admin @ si @ Serial 3722  
Permanent link to this record
 

 
Author Wenjuan Gong; Yue Zhang; Wei Wang; Peng Cheng; Jordi Gonzalez edit  url
openurl 
  Title Meta-MMFNet: Meta-learning-based Multi-model Fusion Network for Micro-expression Recognition Type Journal Article
  Year 2023 Publication ACM Transactions on Multimedia Computing, Communications, and Applications Abbreviated Journal TMCCA  
  Volume (down) 20 Issue 2 Pages 1–20  
  Keywords  
  Abstract Despite its wide applications in criminal investigations and clinical communications with patients suffering from autism, automatic micro-expression recognition remains a challenging problem because of the lack of training data and imbalanced classes problems. In this study, we proposed a meta-learning-based multi-model fusion network (Meta-MMFNet) to solve the existing problems. The proposed method is based on the metric-based meta-learning pipeline, which is specifically designed for few-shot learning and is suitable for model-level fusion. The frame difference and optical flow features were fused, deep features were extracted from the fused feature, and finally in the meta-learning-based framework, weighted sum model fusion method was applied for micro-expression classification. Meta-MMFNet achieved better results than state-of-the-art methods on four datasets. The code is available at https://github.com/wenjgong/meta-fusion-based-method.  
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  Notes ISE Approved no  
  Call Number Admin @ si @ GZW2023 Serial 3862  
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Author Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez edit  doi
openurl 
  Title Solving the Multi Object Occlusion Problem in a Multiple Camera Tracking System Type Journal
  Year 2009 Publication Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume (down) 19 Issue 1 Pages 165-171  
  Keywords  
  Abstract An efficient method to overcome adverse effects of occlusion upon object tracking is presented. The method is based on matching paths of objects in time and solves a complex occlusion-caused problem of merging separate segments of the same path.  
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  Series Volume Series Issue Edition  
  ISSN 1054-6618 ISBN Medium  
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  Notes ISE Approved no  
  Call Number ISE @ ise @ MAR2009a Serial 1160  
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Author A. Diplaros; N. Vlassis; Theo Gevers edit  openurl
  Title A Spatially Constrained Generative Model and an EM Algorithm for Image Segmentation Type Journal
  Year 2007 Publication IEEE Transactions on Neural Networks Abbreviated Journal  
  Volume (down) 18 Issue 3 Pages 798-808  
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  Notes ISE Approved no  
  Call Number Admin @ si @ DVG2007 Serial 947  
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Author A. Pujol; Juan J. Villanueva edit  openurl
  Title A supervised Modification of the Hausdorff distance for visual shape classification Type Journal
  Year 2002 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal  
  Volume (down) 16 Issue 3 Pages 349-359  
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  Abstract (IF: 0.359)  
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  Notes ISE Approved no  
  Call Number PuV2002 Serial 273  
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