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Found 9 papers, 0 papers with code
Benchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches
In the realm of data privacy, the ability to effectively anonymise text is paramount.
Evaluating the Energy Efficiency of Few-Shot Learning for Object Detection in Industrial Settings
In the ever-evolving era of Artificial Intelligence (AI), model performance has constituted a key metric driving innovation, leading to an exponential growth in model size and complexity.
Toward Green and Human-Like Artificial Intelligence: A Complete Survey on Contemporary Few-Shot Learning Approaches
Despite deep learning's widespread success, its data-hungry and computationally expensive nature makes it impractical for many data-constrained real-world applications.
Evaluation of Environmental Conditions on Object Detection using Oriented Bounding Boxes for AR Applications
The objective of augmented reality (AR) is to add digital content to natural images and videos to create an interactive experience between the user and the environment.
Multimodal Explainable Artificial Intelligence: A Comprehensive Review of Methodological Advances and Future Research Directions
The current study focuses on systematically analyzing the recent advances in the field of Multimodal eXplainable Artificial Intelligence (MXAI).
Localization as a key enabler of 6G wireless systems: A comprehensive survey and an outlook
Finally, insights that arise from the presented analysis are summarized and used to highlight the most important future directions for localization in 6G wireless systems.
Large Scale Global Optimization Algorithms for IoT Networks: A Comparative Study
To the best of the authors knowledge, this is the first time that LGSO algorithms are applied to the optimal power allocation problem in IoT networks.
The evolution of argumentation mining: From models to social media and emerging tools
In this survey article, we bridge the gap between theoretical approaches of argumentation mining and pragmatic schemes that satisfy the needs of social media generated data, recognizing the need for adapting more flexible and expandable schemes, capable to adjust to the argumentation conditions that exist in social media.
Smart IoT Cameras for Crowd Analysis based on augmentation for automatic pedestrian detection, simulation and annotation
In order to provide related behavioural models, simulation and tracking approaches have been considered in the literature.
