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pro vyhledávání: '"A, Aslam"'
There is a need for empathetic and coherent responses in automated chatbot-facilitated psychotherapy sessions. This study addresses the challenge of enhancing the emotional and contextual understanding of large language models (LLMs) in psychiatric a
Externí odkaz:
http://arxiv.org/abs/2410.01306
Nowadays, many machine learning (ML) solutions to improve the wireless standard IEEE802.11p for Vehicular Adhoc Network (VANET) are commonly evaluated in the simulated world. At the same time, this approach could be cost-effective compared to real-wo
Externí odkaz:
http://arxiv.org/abs/2409.16968
Coronal mass ejections (CMEs) are solar eruptions that involve large-scale changes to the magnetic topology of an active region. There exists a range of models for CME onset which are based on twisted or sheared magnetic field above a polarity invers
Externí odkaz:
http://arxiv.org/abs/2409.07261
The Standard Model (SM) is lepton flavor universal, and the recent measurements of lepton flavor universality in $B \to (K,K^*)\ell^{+}\ell^{-}$, for $\ell = \mu, \; e$, decays now lie close to the SM predictions. However, this is not the case for th
Externí odkaz:
http://arxiv.org/abs/2409.03388
This paper presents a cascaded control architecture, based on nonlinear dynamic inversion (NDI), for rigid body attitude control. The proposed controller works directly with the rotation matrix parameterization, that is, with elements of the Special
Externí odkaz:
http://arxiv.org/abs/2409.03028
Optimizing QoS in HD Map Updates: Cross-Layer Multi-Agent with Hierarchical and Independent Learning
The data collected by autonomous vehicle (AV) sensors such as LiDAR and cameras is crucial for creating high-definition (HD) maps to provide higher accuracy and enable a higher level of automation. Nevertheless, offloading this large volume of raw da
Externí odkaz:
http://arxiv.org/abs/2408.11605
Human emotion is a complex phenomenon conveyed and perceived through facial expressions, vocal tones, body language, and physiological signals. Multimodal emotion recognition systems can perform well because they can learn complementary and redundant
Externí odkaz:
http://arxiv.org/abs/2408.09035
Reinforcement Learning (RL) algorithms have been used to address the challenging problems in the offloading process of vehicular ad hoc networks (VANET). More recently, they have been utilized to improve the dissemination of high-definition (HD) Maps
Externí odkaz:
http://arxiv.org/abs/2407.21460
Publikováno v:
2024 11th International Conference on Wireless Networks and Mobile Communications (WINCOM)
One effective way to optimize the offloading process is by minimizing the transmission time. This is particularly true in a Vehicular Adhoc Network (VANET) where vehicles frequently download and upload High-definition (HD) map data which requires con
Externí odkaz:
http://arxiv.org/abs/2408.03329
Autor:
Richet, Nicolas, Belharbi, Soufiane, Aslam, Haseeb, Schadt, Meike Emilie, González-González, Manuela, Cortal, Gustave, Koerich, Alessandro Lameiras, Pedersoli, Marco, Finkel, Alain, Bacon, Simon, Granger, Eric
Systems for multimodal emotion recognition (ER) are commonly trained to extract features from different modalities (e.g., visual, audio, and textual) that are combined to predict individual basic emotions. However, compound emotions often occur in re
Externí odkaz:
http://arxiv.org/abs/2407.12927