Zobrazeno 1 - 10
of 1 672
pro vyhledávání: '"A. Ganzha"'
Autor:
Sowinski, Piotr, Lacalle, Ignacio, Vano, Rafael, Palau, Carlos E., Ganzha, Maria, Paprzycki, Marcin
The landscape of computing technologies is changing rapidly, straining existing software engineering practices and tools. The growing need to produce and maintain increasingly complex multi-architecture applications makes it crucial to effectively ac
Externí odkaz:
http://arxiv.org/abs/2410.20984
Autor:
Sowinski, Piotr, Ganzha, Maria
Collaborative mechanisms allow benchmarks to be updated continuously and adjust to the changing requirements and new use cases. This paradigm is employed for example in the field of machine learning, but up until now there were no examples of truly o
Externí odkaz:
http://arxiv.org/abs/2410.12965
Autor:
Danilenka, Anastasiya, Furutanpey, Alireza, Pujol, Victor Casamayor, Sedlak, Boris, Lackinger, Anna, Ganzha, Maria, Paprzycki, Marcin, Dustdar, Schahram
Handling heterogeneity and unpredictability are two core problems in pervasive computing. The challenge is to seamlessly integrate devices with varying computational resources in a dynamic environment to form a cohesive system that can fulfill the ne
Externí odkaz:
http://arxiv.org/abs/2410.09099
This comprehensive survey serves as an indispensable resource for researchers embarking on the journey of fake news detection. By highlighting the pivotal role of dataset quality and diversity, it underscores the significance of these elements in the
Externí odkaz:
http://arxiv.org/abs/2407.02122
As the role of knowledge-based systems in IoT keeps growing, ensuring resource efficiency of RDF stores becomes critical. However, up until now benchmarks of RDF stores were most often conducted with only one dataset, and the differences between the
Externí odkaz:
http://arxiv.org/abs/2406.16412
Over the years, RDF streaming was explored in research and practice from many angles, resulting in a wide range of RDF stream definitions. This variety presents a major challenge in discussing and integrating streaming systems, due to the lack of a c
Externí odkaz:
http://arxiv.org/abs/2311.14540
A considerable number of texts encountered daily are somehow connected with each other. For example, Wikipedia articles refer to other articles via hyperlinks, scientific papers relate to others via citations or (co)authors, while tweets relate via u
Externí odkaz:
http://arxiv.org/abs/2305.11070
RDF data streaming has been explored by the Semantic Web community from many angles, resulting in multiple task formulations and streaming methods. However, for many existing formulations of the problem, reliably benchmarking streaming solutions has
Externí odkaz:
http://arxiv.org/abs/2305.06226
The concept of extended cloud requires efficient network infrastructure to support ecosystems reaching form the edge to the cloud(s). Standard approaches to network load balancing deliver static solutions that are insufficient for the extended clouds
Externí odkaz:
http://arxiv.org/abs/2304.09313
Autor:
Legierski, Jaroslaw, Rachwal, Kajetan, Sowinski, Piotr, Niewolski, Wojciech, Ratuszek, Przemyslaw, Kopertowski, Zbigniew, Paprzycki, Marcin, Ganzha, Maria
Publikováno v:
ICIMMI 2022: Proceedings of the 4th International Conference on Information Management & Machine Intelligence
Detecting Personal Protective Equipment in images and video streams is a relevant problem in ensuring the safety of construction workers. In this contribution, an architecture enabling live image recognition of such equipment is proposed. The solutio
Externí odkaz:
http://arxiv.org/abs/2301.01501