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Chapter and Conference Paper
C2N-ABDP: Cluster-to-Node Attention-Based Differentiable Pooling
Graph neural networks have achieved state-of-the-art performance in various graph based tasks, including classification and regression at both node and graph level. In the context of graph classification, grap...
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Chapter
Genetic Studies of Sarcoptes scabiei: New Tools for Old Questions
The scabies mite, Sarcoptes scabiei, has long been reputed a “diverse” parasite, substructured in an indefinite number of host-related varieties. In the two last decades, this widely accepted view has been put (a...
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Chapter
Sarcoptic Mange in Wild and Domestic Animals
Sarcoptic mange is recognized as a common skin disease caused by Sarcoptes scabiei in a wide range of mammalian species. To date, the infection has been reported from 10 orders, 33 families and 148 species of dom...
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Chapter and Conference Paper
MONstEr: A Deep Learning-Based System for the Automatic Generation of Gaming Assets
In recent years, we have witnessed the spread of computer graphics techniques, used as a background map for movies and video games. Nevertheless, when creating 3D models with conventional computer graphics sof...
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Chapter and Conference Paper
FakeNED: A Deep Learning Based-System for Fake News Detection from Social Media
Social networks are increasingly present in our daily life. They allow us to remain in contact with friends regardless of distances, to share posts, images, videos, to be part of communities or come across art...
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Chapter and Conference Paper
A Novel Graph Kernel Based on the Wasserstein Distance and Spectral Signatures
Spectral signatures have been used with great success in computer vision to characterise the local and global topology of 3D meshes. In this paper, we propose to use two widely used spectral signatures, the He...
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Chapter and Conference Paper
Classifying Me Softly: A Novel Graph Neural Network Based on Features Soft-Alignment
Graph neural networks are increasingly becoming the framework of choice for graph-based machine learning. In this paper we propose a new graph neural network architecture based on the soft-alignment of the gra...
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Chapter and Conference Paper
A Deep Learning-Based System for Product Recognition in Intelligent Retail Environment
This work proposes a pipeline that aims to recognize the products in a shelf, at the level of the single SKU (Stock Kee** Unit), starting from a photo of that shelf. It is composed of a first neural network ...
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Chapter
Migrant Digital Space: Building an Incomplete Map to Navigate Public Online Migration
This chapter introduces the concept of migrant digital space (MDS). MDS is defined as configured by migrants’ online activity before the journey, en route, and when settling down, and as a space shaped by prac...
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Chapter
Caring for (Big) Data: An Introduction to Research Methodologies and Ethical Challenges in Digital Migration Studies
Digital technologies present new methodological and ethical challenges for migration studies: from ensuring data access in ethically viable ways to privacy protection, ensuring autonomy, and security of resear...
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Chapter
Contrapuntal Connectedness: Analysing Relations Between Social Media Data and Ethnography in Digital Migration Studies
This chapter presents a rethinking of the relationship between ethnography and so-called big social data as being comparable to those between a sum and its parts (Strathern 1991/2004). Taking cue from Tim Ingo...
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Chapter and Conference Paper
Estimating the Manifold Dimension of a Complex Network Using Weyl’s Law
The dimension of the space underlying real-world networks has been shown to strongly influence the networks structural properties, from the degree distribution to the way the networks respond to diffusion and ...
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Chapter and Conference Paper
People Counting on Low Cost Embedded Hardware During the SARS-CoV-2 Pandemic
Detecting and tracking people is a challenging task in a persistent crowded environment as retail, airport or station, for human behaviour analysis of security purposes. Especially during the global spread of ...
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Chapter and Conference Paper
The Average Mixing Kernel Signature
We introduce the Average Mixing Kernel Signature (AMKS), a novel signature for points on non-rigid three-dimensional shapes based on the average mixing kernel and continuous-time quantum walks. The average mix...
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Chapter and Conference Paper
GMNet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild
The semantic segmentation of parts of objects in the wild is a challenging task in which multiple instances of objects and multiple parts within those objects must be detected in the scene. This problem remain...
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Chapter
DATA, DATA, AND MORE DATA
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Chapter
FROM DATA TO KNOWLEDGE: HOW MODELS CAN BE USED
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Chapter
COMPUTATIONAL MODELING OF “DISEASE X”
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Chapter
INFECTIOUS DISEASE SPREADING: FROM DATA TO MODELS
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Chapter
THE NUMERICAL FORECAST OF PANDEMIC SPREADING: THE CASE STUDY OF THE 2009 A/H1N1 PDM
