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Laurent Wendling - IEEE Xplore Author Profile
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Laurent Wendling

Also published under: L. Wendling

Publications
41
Citations
454
Publications by Year
19942025
Co-Authors:
Show All Co-Authors (49)
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Laurent Wendling

Also published under: L. Wendling

Affiliation

LIPADE, Université Paris Cité (France)

Publication Topics

Biography

Laurent Wendling received the Ph.D. degree in computer science from University Paul Sabatier, Toulouse, France, in 1997.,From 1993 to 1999, he worked at the Toulouse Institute of Research in Computer Science, in the field of pattern recognition using fuzzy segmentation and graph matching. He is currently an Assistant Professor at the University Henri-Poincare and a member of the ISA research team at the LORIA Laboratory in Nancy. His present research interests are in graphical document analysis and indexing strategy of images.(Based on document published on 7 August 2002).
Publications
41
Citations
454
Publications by Year
19942025
Co-Authors:
Show All Co-Authors (49)
Author's Published Works

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Contrastive Learning of Image Representations Guided by Spatial Relations

Logan Servant;Michaël Clément;Laurent Wendling;Camille Kurtz

2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Year: 2025 | Conference Paper |
The spatial information contained in images is of critical importance for many computer vision tasks. Current state-of-the-art approaches dealing with spatially-related tasks, such as spatial relationship recognition, are typically trained in a supervised manner with semantic information carried by annotations. However, datasets containing spatial relations (such as VisualGenome and SpatialSense) ...Show More

Contrastive Learning of Image Representations Guided by Spatial Relations

Logan Servant;Michaël Clément;Laurent Wendling;Camille Kurtz

Year: 2025 | Conference Paper |

Domain Adaptation for Mapping LCZs in Sub-Saharan Africa With Remote Sensing: A Comprehensive Approach to Health Data Analysis

Basile Rousse;Sylvain Lobry;Géraldine Duthé;Valérie Golaz;Laurent Wendling

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2024 | Volume: 17 | Journal Article |
Cited by: Papers (2)
Environment and population are closely linked, but their interactions remain challenging to assess. To fill this gap, modeling the environment at a fine resolution brings a significant value, if combined with population-based studies. This is particularly challenging in regions where the availability of both population and environmental data are limited. In low- and middle-income countries, many d...Show More

Domain Adaptation for Mapping LCZs in Sub-Saharan Africa With Remote Sensing: A Comprehensive Approach to Health Data Analysis

Basile Rousse;Sylvain Lobry;Géraldine Duthé;Valérie Golaz;Laurent Wendling

Year: 2024 | Volume: 17 | Journal Article |

Transforming Multidimensional Data into Images to Overcome the Curse of Dimensionality

Rebecca Leygonie;Sylvain Lobry;Guillaume Vimont;Laurent Wendling

2023 IEEE International Conference on Image Processing (ICIP)
Year: 2023 | Conference Paper |
When dealing with high-dimensional multivariate time series classification problems, a well-known difficulty is the curse of dimensionality. In this article, we propose an original approach of transposition of multidimensional data into images to tackle the task of classification. We propose a lightweight hybrid model that take this transposed data as an input. This model contains convolutional la...Show More

Transforming Multidimensional Data into Images to Overcome the Curse of Dimensionality

Rebecca Leygonie;Sylvain Lobry;Guillaume Vimont;Laurent Wendling

Year: 2023 | Conference Paper |

Seasonal semi-supervised domain adaptation for linking population studies and Local Climate Zones

Basile Rousse;Sylvain Lobry;Géraldine Duthé;Valérie Golaz;Laurent Wendling

2023 Joint Urban Remote Sensing Event (JURSE)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Environment and demographic dynamics are strongly linked. However, relevant data to study this interaction may be scarce especially in sub-Saharan Africa where it is not always possible to perform such studies with a high temporal frequency. Satellite imagery, when linked to demographic data, can be a significant asset to estimate missing data as it covers every country with both high spatial and ...Show More

Seasonal semi-supervised domain adaptation for linking population studies and Local Climate Zones

Basile Rousse;Sylvain Lobry;Géraldine Duthé;Valérie Golaz;Laurent Wendling

Year: 2023 | Conference Paper |

Embedding Spatial Relations in Visual Question Answering for Remote Sensing

Maxime Faure;Sylvain Lobry;Camille Kurtz;Laurent Wendling

2022 26th International Conference on Pattern Recognition (ICPR)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Remote sensing images carry a wealth of information that is not easily accessible to end-users as it requires strong technical skills and knowledge. Visual Question Answering (VQA), a task that aims at answering an open-ended question in natural language from an image, can provide an easier access to this information. Considering the geographical information contained in remote sensing images, que...Show More

Embedding Spatial Relations in Visual Question Answering for Remote Sensing

Maxime Faure;Sylvain Lobry;Camille Kurtz;Laurent Wendling

Year: 2022 | Conference Paper |

Force Banner for the recognition of spatial relations

Robin Deléarde;Camille Kurtz;Philippe Dejean;Laurent Wendling

2020 25th International Conference on Pattern Recognition (ICPR)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
Studying the spatial organization of objects in images is fundamental to increase both the understanding of a sensed scene and the explainability of the perceived similarity between images. This leads to the fundamental problem of handling spatial relations: given two objects depicted in an image, or two parts in an object, how to extract and describe efficiently their spatial configuration? Dedic...Show More

Force Banner for the recognition of spatial relations

Robin Deléarde;Camille Kurtz;Philippe Dejean;Laurent Wendling

Year: 2021 | Conference Paper |

Local Enlacement Histograms for Historical Drop Caps Style Recognition

Michaël Clément;Mickaël Coustaty;Camille Kurtz;Laurent Wendling

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)
Year: 2017 | Conference Paper |
Cited by: Papers (1)
This article focuses on the specific issue of drop caps image recognition in the context of cultural heritage preservation. Due to their heterogeneity and their weakly structured properties, these historical images represent challenging data. An important aspect in the recognition process of drop caps is their background styles, which can be considered as discriminative features to identify both t...Show More

Local Enlacement Histograms for Historical Drop Caps Style Recognition

Michaël Clément;Mickaël Coustaty;Camille Kurtz;Laurent Wendling

Year: 2017 | Volume: 01 | Conference Paper |

Directional Enlacement Histograms for the Description of Complex Spatial Configurations between Objects

Michaël Clément;Adrien Poulenard;Camille Kurtz;Laurent Wendling

IEEE Transactions on Pattern Analysis and Machine Intelligence
Year: 2017 | Volume: 39, Issue: 12 | Journal Article |
Cited by: Papers (17)
The analysis of spatial relations between objects in digital images plays a crucial role in various application domains related to pattern recognition and computer vision. Classical models for the evaluation of such relations are usually sufficient for the handling of simple objects, but can lead to ambiguous results in more complex situations. In this article, we investigate the modeling of spati...Show More

Directional Enlacement Histograms for the Description of Complex Spatial Configurations between Objects

Michaël Clément;Adrien Poulenard;Camille Kurtz;Laurent Wendling

Year: 2017 | Volume: 39, Issue: 12 | Journal Article |

Bags of spatial relations and shapes features for structural object description

Michaël Clément;Camille Kurtz;Laurent Wendling

2016 23rd International Conference on Pattern Recognition (ICPR)
Year: 2016 | Conference Paper |
Cited by: Papers (4)
We introduce a novel bags-of-features framework based on relative position descriptors, modeling both spatial relations and shape information between the pairwise structural subparts of objects. First, we propose a hierarchical approach for the decomposition of complex objects into structural subparts, as well as their description using the concept of Force Histogram Decomposition (FHD). Then, an ...Show More

Bags of spatial relations and shapes features for structural object description

Michaël Clément;Camille Kurtz;Laurent Wendling

Year: 2016 | Conference Paper |

Detection and analysis of breast masses from MRIs and dual energy contrast enhanced mammography

Soumaya Trabelsi Ben Ameur;Laurent Wendling;Dorra Sellami

2016 International Image Processing, Applications and Systems (IPAS)
Year: 2016 | Conference Paper |
Cited by: Papers (2)
This paper focuses on breast masses analysis from two different modalities: Magnetic Resonance Imaging (MRI) and Dual-Energy Contrast Enhanced Digital Mammography (DECEDM). After the segmentation step, a set of texture and shape features are extracted from both MRI and DECEDM. Then textural and morphological information extracted from the two modalities are combined in order to improve breast canc...Show More

Detection and analysis of breast masses from MRIs and dual energy contrast enhanced mammography

Soumaya Trabelsi Ben Ameur;Laurent Wendling;Dorra Sellami

Year: 2016 | Conference Paper |

Overlaid Arrow Detection for Labeling Regions of Interest in Biomedical Images

K.C. Santosh;Laurent Wendling;Sameer Antani;George R. Thoma

IEEE Intelligent Systems
Year: 2016 | Volume: 31, Issue: 3 | Magazine Article |
Cited by: Papers (48)
A new template-free geometric signature-based technique detects arrow annotations on biomedical images. Arrow detection is a key first step to region-of-interest (ROI) labeling and image content analysis. Images are first binarized using a fuzzy binarization tool, and candidates are selected based on the connected component principle. For each candidate, the proposed method checks geometric proper...Show More

Overlaid Arrow Detection for Labeling Regions of Interest in Biomedical Images

K.C. Santosh;Laurent Wendling;Sameer Antani;George R. Thoma

Year: 2016 | Volume: 31, Issue: 3 | Magazine Article |

On the Scalability of Graphic Symbol Recognition

Jean-Pierre Salmon;Laurent Wendling

2014 22nd International Conference on Pattern Recognition
Year: 2014 | Conference Paper |
This paper deals with a complex symbol recognition process considering a large number of classes and only one training image per class. Furthermore, the response times of recognition system should be short and the interpretation of results must be easy. In this particular case, both statistical and structural methods are not the most suitable. A new composite descriptor and a similarity measure ar...Show More

On the Scalability of Graphic Symbol Recognition

Jean-Pierre Salmon;Laurent Wendling

Year: 2014 | Conference Paper |

Scalable Arrow Detection in Biomedical Images

K.C. Santosh;Laurent Wendling;Sameer K. Antani;George R. Thoma

2014 22nd International Conference on Pattern Recognition
Year: 2014 | Conference Paper |
Cited by: Papers (5)
In this paper, we present a scalable arrow detection technique for biomedical images to support information retrieval systems under the purview of content-based image retrieval (CBIR) and text information retrieval (TIR). The idea primarily follows the criteria based on the geometric properties of the arrow, where we introduce signatures from key points associated with it. To handle this, images a...Show More

Scalable Arrow Detection in Biomedical Images

K.C. Santosh;Laurent Wendling;Sameer K. Antani;George R. Thoma

Year: 2014 | Conference Paper |

Comparison of the spatial organization in colorectal tumors using second-order statistics and functional ANOVA

Maya Alsheh Aliy;Johanne Seguin;Aurélie Fischer;Nathalie Mignet;Laurent Wendling;Thomas Hurtut

2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)
Year: 2013 | Conference Paper |
We propose an automatic method to quantitatively describe the spatial organization governing populations of biological objects, such as cells, which exist in stationary histology images. This quantification is of prime importance when striving to compare different tumoral models in order to evaluate potential therapies. We compare two animal models of colorectal cancer. Our approach is based on th...Show More

Comparison of the spatial organization in colorectal tumors using second-order statistics and functional ANOVA

Maya Alsheh Aliy;Johanne Seguin;Aurélie Fischer;Nathalie Mignet;Laurent Wendling;Thomas Hurtut

Year: 2013 | Conference Paper |

Relation Bag-of-Features for Symbol Retrieval

K.C. Santosh;Laurent Wendling;Bart Lamiroy

2013 12th International Conference on Document Analysis and Recognition
Year: 2013 | Conference Paper |
Cited by: Papers (1)
In this paper, we address a new scheme for symbol retrieval based on relation bag-of-features (BOFs) which are computed between the extracted visual primitives. Our feature consists of pair wise spatial relations from all possible combinations of individual visual primitives. The key characteristic of the overall process is to use topological information to guide directional relations. Consequentl...Show More

Relation Bag-of-Features for Symbol Retrieval

K.C. Santosh;Laurent Wendling;Bart Lamiroy

Year: 2013 | Conference Paper |

Object Description Based on Spatial Relations between Level-Sets

Mickaël Garnier;Thomas Hurtut;Laurent Wendling

2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)
Year: 2012 | Conference Paper |
Cited by: Papers (3)
Object recognition methods usually rely on either structural or statistical description. These methods aim at describing different types of information such as the outer contour, the inner structure or texture effects. Comparing two objects then comes down to averaging different data representations which may be a tricky issue. In this paper, we introduce an object descriptor based on the spatial ...Show More

Object Description Based on Spatial Relations between Level-Sets

Mickaël Garnier;Thomas Hurtut;Laurent Wendling

Year: 2012 | Conference Paper |

Fuzzy integrals for the aggregation of confidence measures in speech recognition

Julie Mauclair;Laurent Wendling;David Janiszek

2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011)
Year: 2011 | Conference Paper |
This paper presents a study on merging confidence measures using fuzzy logic. Instead of the previous approaches using the notion of probability, we propose to observe the uncertainty of the recognition hypotheses and the notion of possibility thanks to fuzzy reasoning. Four different confidence measures are developed, coming from different parts of a speech recognizer. Various merging methods are...Show More

Fuzzy integrals for the aggregation of confidence measures in speech recognition

Julie Mauclair;Laurent Wendling;David Janiszek

Year: 2011 | Conference Paper |

Combining Force Histogram and Discrete Lines to Extract Dashed Lines

Isabelle Debled-Rennesson;Laurent Wendling

2010 20th International Conference on Pattern Recognition
Year: 2010 | Conference Paper |
Cited by: Papers (1)
A new method to extract dashed lines in technical document is proposed in this paper by combining force histogram and discrete lines. The aim is to study the spatial location of couples of connected components using force histogram and to refine the recognition by considering surrounding discrete lines. This new model is fast and it allows a good extraction of occulted patterns in presence of nois...Show More

Combining Force Histogram and Discrete Lines to Extract Dashed Lines

Isabelle Debled-Rennesson;Laurent Wendling

Year: 2010 | Conference Paper |

Using Spatial Relations for Graphical Symbol Description

Santosh K.C.;Laurent Wendling;Bart Lamiroy

2010 20th International Conference on Pattern Recognition
Year: 2010 | Conference Paper |
Cited by: Papers (4)
In this paper, we address the use of unified spatial relations for symbol description. We present a topologically guided directional relation signature. It references a unique point set instead of one entity in a pair, thus avoiding problems related to erroneous choices of reference entities and preserves symmetry. We experimentally validate our method on showing its ability to serve in a symbol r...Show More

Using Spatial Relations for Graphical Symbol Description

Santosh K.C.;Laurent Wendling;Bart Lamiroy

Year: 2010 | Conference Paper |

Evaluation of adaptive FRIFS method through several classification comparisons

Vincent. Bombardier;Laurent Wendling;Emmanuel Schmitt

International Conference on Fuzzy Systems
Year: 2010 | Conference Paper |
An iterative method to select suitable features for pattern recognition context has been proposed (FRIFS). It combines a global feature selection method based on the Choquet integral and a fuzzy linguistic rule classifier. In this paper, enhancements of this method are presented. An automatic step has been added to make it adaptive to process numerous features. The experimental study, made in a wo...Show More

Evaluation of adaptive FRIFS method through several classification comparisons

Vincent. Bombardier;Laurent Wendling;Emmanuel Schmitt

Year: 2010 | Conference Paper |

Document Binarization Based on Connected Operators

Benoit Naegel;Laurent Wendling

2009 10th International Conference on Document Analysis and Recognition
Year: 2009 | Conference Paper |
Cited by: Papers (3)
An original binarization method based on connected operators is proposed in this paper. Connected operators enable to filter and/or segment an image by preserving its contours.The proposed binarization method enables to extract relevant document objects by means of the component-tree structure. This method was compared to other binarization methods and showed good behavior in various contexts.Show More

Document Binarization Based on Connected Operators

Benoit Naegel;Laurent Wendling

Year: 2009 | Conference Paper |

Improving Fuzzy Rule Classifier by Extracting Suitable Features From Capacities With Respect to the Choquet Integral

Emmanuel Schmitt;Vincent Bombardier;Laurent Wendling

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
Year: 2008 | Volume: 38, Issue: 5 | Journal Article |
Cited by: Papers (22)
In this paper, an iterative method to select suitable features in an industrial pattern recognition context is proposed. It combines a global method of feature selection and a fuzzy linguistic rule classifier. It is applied to an industrial fabric textile context. The aim of the global vision system is to identify textile fabric defects. From the related industrial process, the training data sets ...Show More

Improving Fuzzy Rule Classifier by Extracting Suitable Features From Capacities With Respect to the Choquet Integral

Emmanuel Schmitt;Vincent Bombardier;Laurent Wendling

Year: 2008 | Volume: 38, Issue: 5 | Journal Article |

Symbol Recognition Using a 2-class Hierarchical Model of Choquet Integrals

L. Wendling;J. Rendek

Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)
Year: 2007 | Conference Paper |
Cited by: Papers (2)
We present an approach allowing to automatically extract a suitable set of soft output classifiers and to aggregate them to provide a global decision using the Choquet integral. This approach relies on two key points. A learning algorithm based on a 2-class model is performed to define a new set of decisions rules assuming to be experts dedicated to recognize one class from another one. All the as...Show More

Symbol Recognition Using a 2-class Hierarchical Model of Choquet Integrals

L. Wendling;J. Rendek

Year: 2007 | Volume: 2 | Conference Paper |

A feature selection method based on Choquet Integral and Typicality Analysis

Cyril Mazaud;Jan Rendek;Vincent Bombardier;Laurent Wendling

2007 IEEE International Fuzzy Systems Conference
Year: 2007 | Conference Paper |
Cited by: Papers (4)
An iterative feature selection method based on feature typicality and interactivity analysis is presented in this paper. The aim is to enhance model interpretability by selecting the best significant features among a list extracted from images. The inference mechanism uses a fuzzy linguistic rule-based system. This method is applied here to a wood defect classification problem. Nowadays, feature s...Show More

A feature selection method based on Choquet Integral and Typicality Analysis

Cyril Mazaud;Jan Rendek;Vincent Bombardier;Laurent Wendling

Year: 2007 | Conference Paper |

A new method to detect arcs and segments from curvature profiles

J.-P. Salmon;I. Debled-Rennesson;L. Wendling

18th International Conference on Pattern Recognition (ICPR'06)
Year: 2006 | Conference Paper |
Cited by: Papers (7)
In this paper a new method of arc detection based on arithmetic discrete lines is presented. Key points are extracted from such a profile and used for the reconstruction. The used method is fast and easy to implement. Experimental studies on several series of test images show the stability and the robustness of the proposed methodShow More

A new method to detect arcs and segments from curvature profiles

J.-P. Salmon;I. Debled-Rennesson;L. Wendling

Year: 2006 | Volume: 3 | Conference Paper |

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