Zobrazeno 1 - 10
of 24 275
pro vyhledávání: '"Kassem, A."'
Deceptive patterns (DPs) in digital interfaces manipulate users into making unintended decisions, exploiting cognitive biases and psychological vulnerabilities. These patterns have become ubiquitous across various digital platforms. While efforts to
Externí odkaz:
http://arxiv.org/abs/2411.07441
Pedestrian heading tracking enables applications in pedestrian navigation, traffic safety, and accessibility. Previous works, using inertial sensor fusion or machine learning, are limited in that they assume the phone is fixed in specific orientation
Externí odkaz:
http://arxiv.org/abs/2410.06400
With the steadily increasing pedestrian fatalities, pedestrian safety is a growing concern, especially in urban environments. Advanced Driver Assistance Systems (ADAS) have been developed to mitigate road user risks by predicting potential pedestrian
Externí odkaz:
http://arxiv.org/abs/2410.06388
Product attribute value identification (PAVI) involves automatically identifying attributes and their values from product information, enabling features like product search, recommendation, and comparison. Existing methods primarily rely on fine-tuni
Externí odkaz:
http://arxiv.org/abs/2409.12695
Natural distribution shift causes a deterioration in the perception performance of convolutional neural networks (CNNs). This comprehensive analysis for real-world traffic data addresses: 1) investigating the effect of natural distribution shift and
Externí odkaz:
http://arxiv.org/abs/2409.03543
In this work, we explore a time-fractional diffusion equation of order $\alpha \in (0,1)$ with a stochastic diffusivity parameter. We focus on efficient estimation of the expected values (considered as an infinite dimensional integral on the parametr
Externí odkaz:
http://arxiv.org/abs/2409.00893
Privacy policies are crucial in the online ecosystem, defining how services handle user data and adhere to regulations such as GDPR and CCPA. However, their complexity and frequent updates often make them difficult for stakeholders to understand and
Externí odkaz:
http://arxiv.org/abs/2408.14830
Autor:
Schilberth, F., Jiang, M. -C., Mardelé, F. Le, Papp, L. B., Mohelsky, I., Kassem, M. A., Tabata, Y., Waki, T., Nakamura, H., Guo, G. -Y., Orlita, M., Arita, R., Kézsmárki, I., Bordács, S.
Topological magnets exhibit fascinating properties like topologically protected surface states or anomalous transport phenomena. While these properties can be significantly altered by manipulating the magnetic state, the experimental verification of
Externí odkaz:
http://arxiv.org/abs/2408.03575
Autor:
Kaul, Chaitanya, Mitchell, Kevin J., Kassem, Khaled, Tragakis, Athanasios, Kapitany, Valentin, Starshynov, Ilya, Villa, Federica, Murray-Smith, Roderick, Faccio, Daniele
In the field of detection and ranging, multiple complementary sensing modalities may be used to enrich the information obtained from a dynamic scene. One application of this sensor fusion is in public security and surveillance, whose efficacy and pri
Externí odkaz:
http://arxiv.org/abs/2408.00816
Publikováno v:
IEEE Access, vol. 12, pp. 157140-157148, Oct. 25, 2024
The deployment of artificial intelligence (AI) in decision-making applications requires ensuring an appropriate level of safety and reliability, particularly in changing environments that contain a large number of unknown observations. To address thi
Externí odkaz:
http://arxiv.org/abs/2407.19860