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A Late-Fusion Approach to Community Detection in Attributed Networks

Chang Liu, Christine Largeron, Osmar R. Zaïane, Shiva Zamani Gharaghooshi
2020 International Symposium on Intelligent Data Analysis  
The majority of research on community detection in attributed networks follows an "early fusion" approach, in which the structural and attribute information about the network are integrated together as  ...  In this paper, we propose an approach called late-fusion, which looks at this problem from a different perspective.  ...  Conclusion and Future Direction In this paper, we proposed a new approach to the problem of community detection in attributed networks that follows a late-fusion strategy.  ... 
doi:10.1007/978-3-030-44584-3_24 dblp:conf/ida/LiuLZG20 fatcat:wnrwmrf5wjg4hnpau6o4z55xtm

Community detection in node-attributed social networks: a survey [article]

Petr Chunaev
2020 arXiv   pre-print
This belief has motivated the progress in developing community detection methods that use both the structure and the attributes of network (i.e. deal with a node-attributed graph) to yield more informative  ...  Classical approaches for community detection usually deal only with network structure and ignore features of its nodes (called node attributes), although many real-world social networks provide additional  ...  improve the quality of exposition in the survey essentially.  ... 
arXiv:1912.09816v2 fatcat:c6c72vhh7jgbxfdzo3fbps44q4

A modified label propagation algorithm for community detection in attributed networks

Deepanshu Malhotra, Anuradha Chug
2021 International Journal of Information Management Data Insights  
Community detection is an important problem in network science that discovers highly clustered groups of nodes having similar properties.  ...  These variants utilize link strength and node attribute information to enhance the quality of detected communities.  ...  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.  ... 
doi:10.1016/j.jjimei.2021.100030 fatcat:3hizwopqpjayjfa5a5smnmxqii

Exploitation of Semantic Keywords for Malicious Event Classification [article]

Hyungtae Lee and Sungmin Eum and Joel Levis and Heesung Kwon and James Michaelis and Michael Kolodny
2017 arXiv   pre-print
We further show that incorporating the keyword-driven information into early- and late-fusion approaches can significantly enhance malicious event classification.  ...  We first show that by using recently introduced attention models, a naive CNN-based event classifier actually learns to primarily focus on local attributes associated with the discriminant semantic keywords  ...  Early-and late fusion approaches fusion approaches.  ... 
arXiv:1610.06903v2 fatcat:uchwzfrda5b5joar6uxra2wb5q

Detection of Propaganda Techniques in Visuo-Lingual Metaphor in Memes [article]

Sunil Gundapu, Radhika Mamidi
2022 arXiv   pre-print
To detect propaganda in Internet memes, we propose a multimodal deep learning fusion system that fuses the text and image feature representations and outperforms individual models based solely on either  ...  The exponential rise of social media networks has allowed the production, distribution, and consumption of data at a phenomenal rate.  ...  respect to only utilising a single fusion of late (or early) features.  ... 
arXiv:2205.02937v1 fatcat:la3cealfpnfedfxog75beofb2y

Employing Multimodal Machine Learning for Stress Detection

Rahee Walambe, Pranav Nayak, Ashmit Bhardwaj, Ketan Kotecha, Deepak Kumar Jain
2021 Journal of Healthcare Engineering  
The contribution of this work is twofold: firstly, proposing a multimodal AI-based strategy for fusion to detect stress and its level and, secondly, identifying a stress pattern over a period of time.  ...  In this work, a multimodal AI-based framework is proposed to monitor a person's working behavior and stress levels.  ...  NASA-TLX predictions were also carried out with late fusion model but the results were not significant. is can be attributed to the fact that late fusion model had only a few features which were not able  ... 
doi:10.1155/2021/9356452 pmid:34745514 pmcid:PMC8568542 fatcat:x5d5b3k5tzd45pwaahinkyk2ri

Detecting Depression with Word-Level Multimodal Fusion

Morteza Rohanian, Julian Hough, Matthew Purver
2019 Zenodo  
We propose a model that is able to perform modality fusion incrementally after each word in an utterance using a time-dependent recurrent approach in a deep learning set-up.  ...  Our results show the effectiveness of word-level multimodal fusion, achieving state-of-the-art results in depression detection and outperforming early feature-level and late fusion techniques.  ...  model-based approach in which optimal fusion is learned using a neural network.  ... 
doi:10.5281/zenodo.3689458 fatcat:k3m3b7edrbfhfnugcuqejqvzwu

Affect-Aware Deep Belief Network Representations for Multimodal Unsupervised Deception Detection [article]

Leena Mathur, Maja J Matarić
2021 arXiv   pre-print
To address this challenge, we propose the first unsupervised approach for detecting real-world, high-stakes deception in videos without requiring labels.  ...  In addition to using facial affect as a feature on which DBN models are trained, we also introduce a DBN training procedure that uses facial affect as an aligner of audio-visual representations.  ...  late fusion networks, and multimodal affect-aligned networks.  ... 
arXiv:2108.07897v2 fatcat:w5le5b5luzanbnoibjjzkhqfu4

Counteracting the contemporaneous proliferation of digital forgeries and fake news

2019 Anais da Academia Brasileira de Ciências  
To look for authenticity in a wide sea of fake news, every detail is a lead.  ...  Ultimately, we show how new research areas are working to seamlessly stitch together all these methods so as to provide a unified analysis and to establish the synchronization in space and timethe X-Coherence  ...  ACKNOWLEDGMENTS The research for this paper was financially supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), DéjàVu grant #2017/12646-3 and grant #2017/12631-6; by the Coordenação  ... 
doi:10.1590/0001-3765201820180149 fatcat:ebfy7ivfargtthveflq5oq6c44

Visual and Textual Analysis of Social Media and Satellite Images for Flood Detection @ Multimedia Satellite Task MediaEval 2017

Konstantinos Avgerinakis, Anastasia Moumtzidou, Stelios Andreadis, Emmanouil Michail, Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Kompatsiaris
2017 MediaEval Benchmarking Initiative for Multimedia Evaluation  
Visual and textual analysis, as well as late fusion of their similarity scores, were deployed in social media images, while color analysis in the RGB and nearinfrared channel of satellite images was performed  ...  This paper presents the algorithms that CERTH team deployed in order to tackle disaster recognition tasks and more specifically Disaster Image Retrieval from Social Media (DIRSM) and Flood-Detection in  ...  The similarity scores of the two modalities were also combined with the use of a late fusion approach that uses non-linear graph based techniques (random walk, diffusion-based) in a weighted non-linear  ... 
dblp:conf/mediaeval/AvgerinakisMAMG17 fatcat:jj526zempjdydmcz3rmdbgo3tm

Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks [article]

Nicolas Audebert , Sébastien Lefèvre
2017 arXiv   pre-print
Our contributions are threefold: a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, b) we investigate early and late fusion of Lidar  ...  Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity  ...  This data fusion approach can also be adapted to other deep neural networks, such as residual networks as illustrated in Fig. 4b .  ... 
arXiv:1711.08681v1 fatcat:ndaguoumsrdwholmyf6ru56xay

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre
2018 ISPRS journal of photogrammetry and remote sensing (Print)  
Our contributions are three-fold: a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, b) we investigate early and late fusion of Lidar  ...  Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity  ...  Late fusion One caveat of the FuseNet approach is that both streams are expected to be topologically compatible in order to fuse the encoders.  ... 
doi:10.1016/j.isprsjprs.2017.11.011 fatcat:et734k3y3vhe3frej7hulxga6a

Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection [article]

Chengyang Li, Dan Song, Ruofeng Tong, Min Tang
2018 arXiv   pre-print
In this paper, we deeply compare six different convolutional network fusion architectures and analyse their adaptations, enabling a vanilla architecture to obtain detection performances comparable to the  ...  With this in mind, we propose an Illumination-aware Faster R-CNN (IAF RCNN). Specifically, an Illumination-aware Network is introduced to give an illumination measure of the input image.  ...  Min Tang is supported in part by NSFC (61572423,61732015) and Zhejiang Provincial NSFC (LZ16F020003).  ... 
arXiv:1803.05347v2 fatcat:vmaeoqky5ncsbcngbdfeyrfu2m

Complex Networks and Machine Learning: From Molecular to Social Sciences

David Quesada, Maykel Cruz-Monteagudo, Terace Fletcher, Aliuska Duardo-Sanchez, Humbert González-Díaz
2019 Applied Sciences  
Combining complex networks analysis methods with machine learning (ML) algorithms have become a very useful strategy for the study of complex systems in applied sciences.  ...  In this context, we decided to launch one special issue focused on the benefits of using ML and complex network analysis (in combination or separately) to study complex systems in applied sciences.  ...  Lastly, a new algorithm able to detect all regularly equivalent roles in large-scale complex networks was defined.  ... 
doi:10.3390/app9214493 fatcat:ijewsj5frffopknv53icr235h4

Sensor fusion for coastal waters surveillance

Bharat T. Doshi, Lotfi Benmohamed, Philip F. Chimento, Jr., I-Jeng Wang, Belur V. Dasarathy
2005 Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005  
We also analyze the traffic that the field will be expected to handle in order to support network control and coordination, distributed fusion, off-field communication (including queries and responses,  ...  The sensor-sensor communication may be used to communicate results to other sensors so they can correlate the results and use fusion to improve detection probability and reduce false alarm probability.  ...  ACKNOWLEDGMENTS We would like to acknowledge the many discussions and contributions of our colleague Chris Diehl to this work.  ... 
doi:10.1117/12.603624 fatcat:s3cvae4gm5gxdjwgyqjqnstlim
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