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- surveyApril 2024
Semantic Data Integration and Querying: A Survey and Challenges
- Maroua Masmoudi,
- Sana Ben Abdallah Ben Lamine,
- Mohamed Hedi Karray,
- Bernard Archimede,
- Hajer Baazaoui Zghal
ACM Computing Surveys (CSUR), Volume 56, Issue 8Article No.: 209, Pages 1–35https://doi.org/10.1145/3653317Digital revolution produces massive, heterogeneous and isolated data. These latter remain underutilized, unsuitable for integrated querying and knowledge discovering. Hence the importance of this survey on data integration which identifies challenging ...
- ArticleMarch 2024
Play Everywhere: A Temporal Logic Based Game Environment Independent Approach for Playing Soccer with Robots
AbstractRobots playing soccer often rely on hard-coded behaviors that struggle to generalize when the game environment change. In this paper, we propose a temporal logic based approach that allows robots’ behaviors and goals to adapt to the semantics of ...
- research-articleApril 2023
The PLASMA Framework: Laying the Path to Domain-Specific Semantics in Dataspaces
WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023April 2023, Pages 1474–1479https://doi.org/10.1145/3543873.3587662Modern data management is evolving from centralized integration-based solutions to a non-integration-based process of finding, accessing and processing data, as observed within dataspaces. Common reference dataspace architectures assume that sources ...
- research-articleOctober 2022
DocSemMap 2.0: Semantic Labeling based on Textual Data Documentations Using Seq2Seq Context Learner
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementOctober 2022, Pages 98–107https://doi.org/10.1145/3511808.3557446Methods for automated semantic labeling of data are an indispensable basis for increasing the usability of data. On the one hand, they contribute to the homogenization of the annotations and thus to the increase in quality; on the other hand, they ...
- research-articleOctober 2021
Co-Transport for Class-Incremental Learning
MM '21: Proceedings of the 29th ACM International Conference on MultimediaOctober 2021, Pages 1645–1654https://doi.org/10.1145/3474085.3475306Traditional learning systems are trained in closed-world for a fixed number of classes, and need pre-collected datasets in advance. However, new classes often emerge in real-world applications and should be learned incrementally. For example, in ...
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- tutorialOctober 2021
Computer Vision for Autonomous UAV Flight Safety: An Overview and a Vision-based Safe Landing Pipeline Example
- Efstratios Kakaletsis,
- Charalampos Symeonidis,
- Maria Tzelepi,
- Ioannis Mademlis,
- Anastasios Tefas,
- Nikos Nikolaidis,
- Ioannis Pitas
ACM Computing Surveys (CSUR), Volume 54, Issue 9Article No.: 181, Pages 1–37https://doi.org/10.1145/3472288Recent years have seen an unprecedented spread of Unmanned Aerial Vehicles (UAVs, or “drones”), which are highly useful for both civilian and military applications. Flight safety is a crucial issue in UAV navigation, having to ensure accurate compliance ...
- research-articleAugust 2021
Supervoxel Convolution for Online 3D Semantic Segmentation
ACM Transactions on Graphics (TOG), Volume 40, Issue 3Article No.: 34, Pages 1–15https://doi.org/10.1145/3453485Online 3D semantic segmentation, which aims to perform real-time 3D scene reconstruction along with semantic segmentation, is an important but challenging topic. A key challenge is to strike a balance between efficiency and segmentation accuracy. There ...
- research-articleJuly 2021
Lifelog Image Retrieval Based on Semantic Relevance Mapping
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 17, Issue 3Article No.: 92, Pages 1–18https://doi.org/10.1145/3446209Lifelog analytics is an emerging research area with technologies embracing the latest advances in machine learning, wearable computing, and data analytics. However, state-of-the-art technologies are still inadequate to distill voluminous multimodal ...
- research-articleJune 2021
Research on Real-Time Semantic SLAM Based on Object Detection Network
ICRAI '20: Proceedings of the 6th International Conference on Robotics and Artificial IntelligenceNovember 2020, Pages 19–25https://doi.org/10.1145/3449301.3449306Simultaneous localization and mapping (SLAM) is an important technology in the field of robotics. Semantic SLAM can provide a more accurate localization and satisfy the needs of complex applications, which has become a research hot spot. In this paper, ...
- research-articleOctober 2020
A Tightly-coupled Semantic SLAM System with Visual, Inertial and Surround-view Sensors for Autonomous Indoor Parking
MM '20: Proceedings of the 28th ACM International Conference on MultimediaOctober 2020, Pages 2691–2699https://doi.org/10.1145/3394171.3413867The semantic SLAM (simultaneous localization and mapping) system is an indispensable module for autonomous indoor parking. Monocular and binocular visual cameras constitute the basic configuration to build such a system. Features used in existing SLAM ...
- research-articleApril 2019
An automated framework creating parametric BIM from GIS data to support design decisions
SIMAUD '19: Proceedings of the Symposium on Simulation for Architecture and Urban DesignApril 2019, Article No.: 4, Pages 1–7GIS has been primarily used for urban scale projects. On the other hand, BIM has been mainly used for building scale projects. Understanding surrounding site context is essential in building design. Thus, architects often utilize GIS data to build 3D ...
- research-articleSeptember 2017
Learning from Internet: Handling Uncertainty in Robotic Environment Modeling
Internetware '17: Proceedings of the 9th Asia-Pacific Symposium on InternetwareSeptember 2017, Article No.: 7, Pages 1–9https://doi.org/10.1145/3131704.3131712Uncertainty is a great challenge for environment perception of autonomous robots. For instance, while building semantic maps (i.e., maps with semantic labels such as object names), the robot may encounter unexpected objects of which it has no knowledge. ...
- research-articleFebruary 2017
Robot@Home, a robotic dataset for semantic mapping of home environments
International Journal of Robotics Research (RBRS), Volume 36, Issue 22 2017, Pages 131–141https://doi.org/10.1177/0278364917695640This paper presents the Robot-at-Home dataset Robot@Home, a collection of raw and processed sensory data from domestic settings aimed at serving as a benchmark for semantic mapping algorithms through the categorization of objects and/or rooms. The ...
- research-articleJanuary 2017
Multimodal learning and inference from visual and remotely sensed data
International Journal of Robotics Research (RBRS), Volume 36, Issue 1Jan 2017, Pages 24–43https://doi.org/10.1177/0278364916679892Autonomous vehicles are often tasked to explore unseen environments, aiming to acquire and understand large amounts of visual image data and other sensory information. In such scenarios, remote sensing data may be available a priori, and can help to build ...
- articleNovember 2016
A new ontology-based multi agent framework for intrusion detection
International Journal of Communication Systems (IJOCS), Volume 29, Issue 17November 2016, Pages 2490–2502https://doi.org/10.1002/dac.3189Ontologies play an essential role in knowledge sharing and exploration, especially in multiagent systems. Intrusion is an unauthorized activity in a network, which is achieved by either active manner information gathering or passive manner harmful ...
- research-articleSeptember 2015
Entity Linking in Queries: Tasks and Evaluation
ICTIR '15: Proceedings of the 2015 International Conference on The Theory of Information RetrievalSeptember 2015, Pages 171–180https://doi.org/10.1145/2808194.2809473Annotating queries with entities is one of the core problem areas in query understanding. While seeming similar, the task of entity linking in queries is different from entity linking in documents and requires a methodological departure due to the ...
- ArticleApril 2015
An Inferring Semantic System Based on Relational Models for Mobile Robotics
ICARSC '15: Proceedings of the 2015 IEEE International Conference on Autonomous Robot Systems and CompetitionsApril 2015, Pages 83–88https://doi.org/10.1109/ICARSC.2015.22Nowadays, there are many robots with the ability to move along its environment and they need a navigation system. In the semantic navigation paradigm, the ability to reason and to infer new knowledge is required. In this work a relational database is ...
- ArticleAugust 2014
Semantic Urban Maps
ICPR '14: Proceedings of the 2014 22nd International Conference on Pattern RecognitionAugust 2014, Pages 4050–4055https://doi.org/10.1109/ICPR.2014.694A novel region based 3D semantic mapping method is proposed for urban scenes. The proposed Semantic Urban Maps (SUM) method labels the regions of segmented images into a set of geometric and semantic classes simultaneously by employing a Markov Random ...
- ArticleApril 2013
Grounding linked open data in wordnet: the case of the OSM semantic network
W2GIS'13: Proceedings of the 12th international conference on Web and Wireless Geographical Information SystemsApril 2013, Pages 1–15https://doi.org/10.1007/978-3-642-37087-8_1In recent years, the open data (LOD) paradigm has emerged as a promising approach to structuring, publishing, and sharing data online, using Semantic Web standards. From a geospatial perspective, one of the key challenges consists of bridging the gap ...
- abstractMarch 2013
Interactive object modeling & labeling for service robots
HRI '13: Proceedings of the 8th ACM/IEEE international conference on Human-robot interactionMarch 2013, Pages 421–422We present an interactive object modeling and labeling system for service robots. The system enables a user to interactively create object models for a set of objects. Users also provide a label for each object, allowing it to be referenced later. ...