Ilias Gialampoukidis

The Centre for Research and Technology, Hellas · Information Technologies Institute (ITI)

Monitoring terrorist groups and their suspicious activities in social media is a challenging task, given the large amounts of data involved and the need to identify the most influential users in a smart way. To this end, many efforts have focused on using centrality measures for the identification of the key players in terrorism-related social medi...

Nowadays there is an important need by journalists and media monitoring companies to cluster news in large amounts of web articles, in order to ensure fast access to their topics or events of interest. Our aim in this work is to identify groups of news articles that share a common topic or event, without a priori knowledge of the number of clusters...

Effective multimedia retrieval requires the combination of the heterogeneous media contained within multimedia objects and the features that can be extracted from them. To this end, we extend a unifying framework that integrates all well-known weighted, graph-based, and diffusion-based fusion techniques that combine two modalities (textual and visu...

This paper presents VERGE interactive search engine, which is capable of browsing and searching into video content. The system integrates content-based analysis and retrieval modules such as video shot segmentation, concept detection, clustering, as well as visual similarity and object-based search.

The detection of complex formations, initially suspected to be oil spills, is investigated using atmospherically corrected multispectral satellite images and deep learning techniques. Several formations have been detected in an inland lake in Northern Greece. Four atmospheric corrections (ACOLITE, iCOR, Polymer, and C2RCC) that are specifically des...

Satellite data are extensively used for water quality monitoring purposes, offering a significantly reduced cost compared to in situ data sampling. Using past measurements to predict future conditions remains a challenging task, because of the complexity of the natural phenomena that are involved, with great potential in terms of water resources ma...

The detection of complex formations, initially suspected to be oil spills, is investigated using atmospherically corrected multi-spectral satellite images and deep learning techniques. Several formations have been detected in an inland lake in Northern Greece. Four atmospheric corrections (ACOLITE, iCOR, Polymer, and C2RCC) that are specifically de...

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due t...

With the constant growth of social media in our daily lives, a huge amount of information is generated online by multiple social networks. However, what can we actually extract with the science of social media sensing? It is a very challenging task to mine meaningful data out of this vast crowdsourcing volume, which also rapidly changes or ends up...

With the increasing prevalence of AI, significant advancements have been made across various domains, such as healthcare, learning, industry, etc. However, challenges persist in terms of trusting and comprehending the outcomes generated by these technologies. Specifically in the language learning domain, teachers face challenges regarding the class...

Three-dimensional (3D) retrieval of objects and models plays a crucial role in many application areas, such as industrial design, medical imaging, gaming and virtual and augmented reality. Such 3D retrieval involves storing and retrieving different representations of single objects, such as images, meshes or point clouds. Early approaches considere...

This paper presents VERGE, an interactive video content retrieval system designed for browsing a collection of images extracted from videos and conducting targeted content searches. VERGE incorporates a variety of retrieval methods, fusion techniques, and reranking capabilities. It also offers a user-friendly web application for query formulation a...

Nowadays, large quantities of multimedia data are generated by various applications on smartphones, drones and other devices. Facilitating retrieval from these multimedia collections requires (a) effective media representation and (b) efficient indexing and query processing approaches. Recently, the MuseHash approach was proposed, which can effecti...

Vibrations are a common issue in the machining and metal-cutting sector, in which the spindle vibration is primarily responsible for the poor surface quality of workpieces. The consequences range from the need to manually finish the metal surfaces, resulting in time-consuming and costly operations, to high scrap rates, with the corresponding waste...

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector, are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due...

Over the past decade, Knowledge Graphs (KGs) gained significant attention as a powerful method for knowledge representation. Driven by increasing interest, a paradigm shift has occurred, where the technology of KGs has transitioned from the research domain to the industry and public sector, with companies and organizations increasingly representing...

The quality of drinking water is a critical factor for public health and the environment. Inland drinking water reservoirs are essential sources of freshwater supply for many communities around the world. However, these reservoirs are susceptible to various forms of contamination, including the presence of muddy water, which can pose significant ch...

Modern Internet connectivity provides the ability to perform efficient communications between the control centre of a healthcare system and the internal management processes of the emergency departments in clinics. Based on this, resource management is improved when exploiting the available efficient connectivity for adapting to the operating state...

Production lines in manufacturing environments benefit from quality diagnosis methods 1 based on learning techniques since their ability to adapt to the runtime conditions improves perfor-2 mance, and at the same time, difficult computational problems are solved in realtime. Predicting the 3 divergence of product physical parameters from an accepta...

This paper discusses the importance of detecting breaking events in real time to help emergency response workers, and how social media can be used to process large amounts of data quickly. Most event detection techniques have focused on either images or text, but combining the two can improve performance. The authors present lessons learned from th...

Deep learning methods are widely used in the domain of change detection in remote sensing images. While datasets of that kind are abundant, annotated images, specific for the task at hand, are still scarce. Neural networks trained with Self supervised learning aim to harness large volumes of unlabeled satellite high resolution images to help in fin...

This paper describes VERGE, an interactive video retrieval system for browsing a collection of images from videos and searching for specific content. The system utilizes many retrieval techniques as well as fusion and reranking capabilities. A Web Application is also part of VERGE, where a user can create queries, view the top results and submit th...

The past few years have seen an accelerating integration of deep learning (DL) techniques into various remote sensing (RS) applications, highlighting their power to adapt and achieving unprecedented advancements. In the present review, we provide an exhaustive exploration of the DL approaches proposed specifically for the spatial downscaling of RS...

Infrastructure monitoring and rapid quality diagnosis comprise the key solutions to achieve zero-defect smart manufacturing. The most fundamental systems in manufacturing industries are computer numerical controlled (CNC) tools. Automating and optimizing their functionality is a highly challenging task because complex dynamics and non-linear relati...

Nowadays, manufacturing companies are eager to access insights from advanced analytics, without requiring them to have specialized IT workforce or data science advanced skills. Most of current solutions lack of easy-to-use advanced data preparation, production reporting and advanced analytics and prediction. Thanks to the increase in the use of sen...

The necessity of organising big streams of Earth Observation (EO) data induces the efficient clustering of image patches, deriving from satellite imagery, into groups. Since the different concepts of the satellite image patches are not known a priori, DBSCAN-Martingale can be applied to estimate the number of the desired clusters. In this paper we...

Flooding is one of the most destructive natural phenomena that happen worldwide, leading to the damage of property and infrastructure or even the loss of lives. The escalation in the intensity and number of flooding events as a result of the combination of climate change and anthropogenic factors motivates the need to adopt real-time solutions for...

Manufacturing companies increasingly become “smarter” as a result of the Industry 4.0 revolution. Multiple sensors are used for industrial monitoring of machines and workers in order to detect events and consequently improve the manufacturing processes, lower the respective costs, and increase safety. Multisensor systems produce big amounts of hete...

Disaster risks related to natural hazards are evolving gradually, albeit accelerating over time, the human-made and cyber threats are changing rapidly exploiting the increasing progress in technologies and the complex, highly interlinked, modern environment of critical infrastructures. Therefore, as these threats have been intensifying, the actions...

The increase of social media use in recent years has shown potential also for the identification of specific trends in the data that could be used to locate earthquakes. In this work, we implemented a pipeline that uses Twitter data to identify locations of earthquakes and use the information to trigger EO data analysis. We tested the pipeline for...

This paper presents VERGE, an interactive video search engine that integrates multiple retrieval methodologies and also combines them with reranking and fusion techniques. Moreover, a user interface, implemented as a Web application, enables users to formulate queries, view the top retrieved shots and watch the respective videos, before submitting...

Social media play an important role in the daily life of people around the globe and users have emerged as an active part of news distribution as well as production. The threatening pandemic of COVID-19 has been the lead subject in online discussions and posts, resulting to large amounts of related social media data, which can be utilised to reinfo...

Discovering potential concepts and events by analyzing Earth Observation (EO) data may be supported by fusing other distributed data sources such as non-EO data, for instance, in-situ citizen observations from social media. The retrieval of relevant information based on a target query or event is critical for operational purposes, for example, to m...

Earth Observation (EO) Big Data Collections are acquired at large volumes and variety, due to their high heterogeneous nature. The multimodal character of EO Big Data requires effective combination of multiple modalities for similarity search. We propose a late fusion mechanism of multiple rankings to combine the results from several uni-modal sear...

This paper presents VERGE, an interactive video search engine that supports efficient browsing and searching into a collection of images or videos. The framework involves a variety of retrieval approaches as well as reranking and fusion capabilities. A Web application enables users to create queries and view the results in a fast and friendly manne...

Discovering potential concepts and events by analyzing Earth Observation (EO) data may be supported by fusing other distributed data sources such as non-EO data, for instance, in-situ citizen observations from social media. The retrieval of relevant information based on a target query or event is critical for operational purposes, for example, to m...

During the last decades, massive amounts of satellite images are becoming available that can be enriched with semantic annotations for the creation of value-added Earth Observation products. One challenge is to extract knowledge from the raw satellite data in an automated way and to effectively manage the extracted information in a semantic way, to...

Recent developments in remote sensing have shown that snow depth can be estimated accurately on a global scale using satellite images through cross-polarization and copolarization backscatter measurements. This method does, however, have some limitations in low-land areas with dense forest coverage and shallow snow, which are often found nearby urb...

This paper demonstrates VERGE, an interactive video retrieval engine for browsing a collection of images or videos and searching for specific content. The engine integrates a multitude of retrieval methodologies that include visual and textual searches and further capabilities such as fusion and reranking. All search options and results appear in a...

Density-based clustering is an effective clustering approach that groups together dense patterns in low- and high-dimensional vectors, especially when the number of clusters is unknown. Such vectors are obtained for example when computer scientists represent unstructured data and then groups them into clusters in an unsupervised way. Another facet...

Towards meeting both challenges of big multimedia data such as scalability and diversity, this chapter presents the state‐of‐the‐art techniques in multimodal fusion of heterogeneous sources of data. It explores both weakly supervised and semi‐supervised approaches that minimize the complexity of the designed systems as well as maximizing their scal...

EOPEN (https://eopen-project.eu/) is a project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the topic EO Big Data Shift in 2017 and has a duration of 3 years, starting from November 2017. In this work, we present the concept of the project, its objectives and the lessons learnt after almo...

Artificial Intelligence (AI) technologies are getting deeper and deeper into remote sensing and satellite image processing offering value-added products and services in a real-time manner. Deep learning techniques applied on visual content are able to infer accurate decisions about concepts and events in an automatic way, based on Deep Convolutiona...

This paper presents the algorithms that CERTH-ITI team deployed to tackle flood detection and road passability from social media and satellite data. Computer vision and deep learning techniques are combined in order to analyze social media and satellite images, while word2vec is used to analyze textual data. Multimodal fusion is also deployed in CE...

Analysts and journalists face the problem of having to deal with very large, heterogeneous, and multilingual data volumes that need to be analyzed, understood, and aggregated. Automated and simplified editorial and authoring process could significantly reduce time, labor, and costs. Therefore, there is a need for unified access to multilingual and...

In every disaster time is the enemy and getting accurate and helpful real-time information for supporting decision support is critical. Data sources for Risk Management Platforms are heterogeneous. This includes data coming from several resources: sensors, social media, the general public and first responders. All this data needs to be analyzed, ag...

Social media are widely used by terrorist organizations and extremist groups for disseminating propaganda and recruiting new members. Given the recent pledges both by the major social media platforms and governments towards combating online terrorism, our work aims at understanding the terrorism-related content posted on social media and distinguis...

Disaster monitoring based on social media posts has raised a lot of interest in the domain of computer science the last decade, mainly due to the wide area of applications in public safety and security and due to the pervasiveness not solely on daily communication but also in life-threating situations. Social media can be used as a valuable source...

The identification of flooded areas over Earth Observation (EO) satellite images has paved the way to monitor damaged areas and take effective actions. Classifying all pixels of a satellite image as a flooded area or not allows for creating maps which are then used by civil protection agencies and first responders. In this work, a method, firstly i...

Collaborative filtering recommenders leverage past user-item ratings in order to predict ratings for new items. One of the most critical steps in such methods corresponds to the formation of the neighbourhood that contains the most similar users or items, so that the ratings associated with them can be employed for predicting new ratings. This work...

The poster presents an overview of the EOPEN project (H2020-776019) funded by the European Commission. Details can be found on the project website: http://eopen-project.eu/

Heterogeneous sources of information, such as images, videos, text and metadata are often used to describe different or complementary views of the same multimedia object, especially in the online news domain and in large annotated image collections. The retrieval of multimedia objects, given a multimodal query, requires the combination of several s...

Large amounts of social media posts are produced on a daily basis and monitoring all of them is a challenging task. In this direction we demonstrate a topic detection and visualisation tool in Twitter data, which filters Twitter posts by topic or keyword, in two different languages; German and Turkish. The system is based on state-of-the-art news c...

Nowadays, a large amount of text documents are produced on a daily basis, so we need efficient and effective access to their content. News articles, blogs and technical reports are often lengthy, so the reader needs a quick overview of the underlying content. To that end we present graph-based models for keyword extraction, in order to compare the...

The increasing amount of image databases over the last years has highlighted our need to represent an image collection efficiently and quickly. The majority of image retrieval and image clustering approaches has been based on the construction of a visual vocabulary in the so called Bag-of-Visual-words (BoV) model, analogous to the Bag-of-Words (BoW...