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Found 29 papers, 0 papers with code
Social Media and Artificial Intelligence for Sustainable Cities and Societies: A Water Quality Analysis Use-case
To ensure the quality of water, different methods for monitoring and assessing the water networks, such as offline and online surveys, are used.
Stylometry Analysis of Multi-authored Documents for Authorship and Author Style Change Detection
This paper investigates three key tasks of style analysis: (i) classification of single and multi-authored documents, (ii) single change detection, which involves identifying the point where the author switches, and (iii) multiple author-switching detection in multi-authored documents.
Document Provenance and Authentication through Authorship Classification
In this paper, we propose an ensemble-based text-processing framework for the classification of single and multi-authored documents, which is one of the key tasks in style analysis.
Relevance Classification of Flood-related Twitter Posts via Multiple Transformers
In recent years, social media has been widely explored as a potential source of communication and information in disasters and emergency situations.
Floods Relevancy and Identification of Location from Twitter Posts using NLP Techniques
This paper presents our solutions for the MediaEval 2022 task on DisasterMM.
A Late Fusion Framework with Multiple Optimization Methods for Media Interestingness
The extraction of such meaningful information is a complex task and generally, the performance of individual algorithms is very low.
Exploration and Exploitation in Federated Learning to Exclude Clients with Poisoned Data
The remaining cluster with surviving clients is then used for training the best FL model (i. e., remaining FL model).
An Explainable Regression Framework for Predicting Remaining Useful Life of Machines
The task is treated as a regression problem where Machine Learning (ML) algorithms are used to predict the RUL of machine components.
Social Media as an Instant Source of Feedback on Water Quality
We also provide an evaluation of the individual models where the highest F1-score of 0. 81 is obtained with the BERT model.
NLP Techniques for Water Quality Analysis in Social Media Content
This paper presents our contributions to the MediaEval 2021 task namely "WaterMM: Water Quality in Social Multimedia".
Visual Sentiment Analysis: A Natural DisasterUse-case Task at MediaEval 2021
The Visual Sentiment Analysis task is being offered for the first time at MediaEval.
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions
These vulnerabilities allow adversaries to launch a diversified set of adversarial attacks on these algorithms in different applications of social media text processing.
Explainable Event Recognition
The results of the study indicate that 78%, 84%, and 78% of the model decisions on natural disasters, sports, and social events datasets, respectively, are based onevent-related objects or regions.
Artificial Intelligence Based Prognostic Maintenance of Renewable Energy Systems: A Review of Techniques, Challenges, and Future Research Directions
To this aim, complex Data Analytics and Machine Learning (ML) techniques are being used to increase the overall efficiency of these prognostic maintenance systems.
The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions
In this paper, we provide a comprehensive overview of different aspects of AI and Big Data in Industry 4. 0 with a particular focus on key applications, techniques, the concepts involved, key enabling technologies, challenges, and research perspective towards deployment of Industry 5. 0.
Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset
In this work, we propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding on the development and training of AI models for automatic sentiment analysis of users' reviews.
Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge
Despite significant improvements over the last few years, cloud-based healthcare applications continue to suffer from poor adoption due to their limitations in meeting stringent security, privacy, and quality of service requirements (such as low latency).
The Diabetic Buddy: A Diet Regulator andTracking System for Diabetics
In this regard, there is a need to build automatic tools to monitor the blood glucose levels of diabetics and their daily food intake.
Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges
In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical (data and algorithmic) challenges to a successful deployment of AI in human-centric applications, with a particular emphasis on the convergence of these concepts/challenges.
Floods Detection in Twitter Text and Images
The extracted features are then used to train multiple individual classifiers whose scores are then combined in a late fusion manner achieving an F1-score of 0. 75%.
Flood Detection via Twitter Streams using Textual and Visual Features
The paper presents our proposed solutions for the MediaEval 2020 Flood-Related Multimedia Task, which aims to analyze and detect flooding events in multimedia content shared over Twitter.
Fake News Detection in Social Media using Graph Neural Networks and NLP Techniques: A COVID-19 Use-case
On the binary classification, the BoW and BERT based solutions obtained an average F1-score of . 666% and . 693%, respectively.
Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services
Most of the research on Federated Learning (FL) has focused on analyzing global optimization, privacy, and communication, with limited attention focusing on analyzing the critical matter of performing efficient local training and inference at the edge devices.
Visual Sentiment Analysis from Disaster Images in Social Media
While sentiment analysis of text streams has been widely explored in literature, sentiment analysis from images and videos is relatively new.
Kalman Filter Based Multiple Person Head Tracking
For multi-target tracking, target representation plays a crucial rule in performance.
Deriving Emotions and Sentiments from Visual Content: A Disaster Analysis Use Case
Sentiment analysis aims to extract and express a person's perception, opinions and emotions towards an entity, object, product and a service, enabling businesses to obtain feedback from the consumers.
Sentiment Analysis from Images of Natural Disasters
Social media have been widely exploited to detect and gather relevant information about opinions and events.
Multi-Modal Machine Learning for Flood Detection in News, Social Media and Satellite Sequences
In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Social Media andsatellites.
Active Learning for Event Detection in Support of Disaster Analysis Applications
Disaster analysis in social media content is one of the interesting research domains having abundance of data.
