@inproceedings {42546,
	title = {ICDAR{\textquoteright}22: Intelligent Cross-Data Analysis and Retrieval},
	journal = {2022 International Conference on Multimedia Retrieval},
	year = {2022},
	month = {06/2022},
	publisher = {ACM},
	address = {2022, Newark, NJ, USA},
	abstract = {We have witnessed the rise of cross-data against multimodal dataproblems recently. The cross-modal retrieval system uses a textualquery to look for images; the air quality index can be predictedusing lifelogging images; the congestion can be predicted usingweather and tweets data; daily exercises and meals can help topredict the sleeping quality are some examples of this researchdirection. Although vast investigations focusing on multimodal dataanalytics have been developed, few cross-data (e.g., cross-modaldata, cross-domain, cross-platform) research has been carried on.In order to promote intelligent cross-data analytics and retrievalresearch and to bring a smart, sustainable society to human beings,the specific article collection on "Intelligent Cross-Data Analysisand Retrieval" is introduced. This Research Topic welcomes thosewho come from diverse research domains and disciplines such aswell-being, disaster prevention and mitigation, mobility, climatechange, tourism, healthcare, and food computing.},
	author = {Dao, Minh-Son and Riegler, Michael and Dang-Nguyen, Duc-Tien and Gurrin, Cathal and Nakashima, Yuta and Dong, Mianxiong}
}
@inproceedings {28095,
	title = {Dutkat: A Multimedia System for Catching Illegal Catchers in a Privacy-Preserving Manner},
	journal = {Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR{\textquoteright}21)},
	year = {2021},
	pages = {57-61},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {Fish crime is considered a global and serious problem for a healthy and sustainable development of one of mankind{\textquoteright}s important sources of food. Technological surveillance and control solutions are emerging as remedies to combat criminal activities, but such solutions might also come with impractical and negative side-effects and challenges. In this paper, we present the concept and design of a surveillance system in lieu of current surveillance trends striking a delicate balance between privacy of legal actors while simultaneously capturing evidence-based footage, sensory data, and forensic proofs of illicit activities. Our proposed novel approach is to assist human operators in the 24/7 surveillance loop of remote professional fishing activities with a privacy-preserving Artificial Intelligence (AI) surveillance system operating in the same proximity as the activities being surveyed. The system will primarily be using video surveillance data, but also other sensor data captured on the fishing vessel. Additionally, the system correlates with other sources such as reports from other fish catches in the approximate area and time, etc. Only upon true positive flagging of specific potentially illicit activities by the locally executing AI algorithms, can forensic evidence be accessed from this physical edge, the fishing vessel. Besides a more privacy-preserving solution, our edge-based AI system also benefits from much less data that has to be transferred over unreliable, low-bandwidth satellite-based networks.},
	isbn = {9781450385299},
	doi = {10.1145/346394410.1145/3463944.3469102},
	url = {https://dl.acm.org/doi/proceedings/10.1145/3463944},
	author = {Tor-Arne Schmidt {Nordmo} and Aril B. {Ovesen} and H{\r a}vard D. {Johansen} and Riegler, Michael and Halvorsen, P{\r a}l and Johansen, Dag},
	editor = {Dao, Minh-Son and Dang-Nguyen, Duc-Tien and Riegler, Michael}
}
@inproceedings {24990,
	title = {Smart Lifelogging: Recognizing Human Activities using PHASOR},
	journal = {Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods},
	year = {2017},
	month = {02/2017},
	pages = {761-768},
	publisher = {Spinger},
	address = {Portugal},
	isbn = {978-989-758-222-6},
	doi = {10.5220/0006320907610768},
	author = {Dang-Nguyen, Duc-Tien and Dao, Minh-Son and Riegler, Michael and Gurrin, Cathal},
	editor = {De Marsico, Maria and Gabriella Sanniti {di Baja} and Fred, Ana}
}
