Zobrazeno 1 - 10
of 2 222
pro vyhledávání: '"A, Koubâa"'
Autor:
Nacar, Omer, Abdelkader, Mohamed, Ghouti, Lahouari, Gabr, Kahled, Al-Batati, Abdulrahman S., Koubaa, Anis
This paper tackles the challenge of real-time 3D trajectory prediction for UAVs, which is critical for applications such as aerial surveillance and defense. Existing prediction models that rely primarily on position data struggle with accuracy, espec
Externí odkaz:
http://arxiv.org/abs/2410.23305
In the field of sensor fusion and state estimation for object detection and localization, ensuring accurate tracking in dynamic environments poses significant challenges. Traditional methods like the Kalman Filter (KF) often fail when measurements ar
Externí odkaz:
http://arxiv.org/abs/2410.10409
Autor:
Koubaa, Amine
Let $X$ be a regular scheme over $\textrm{Spec}(\mathbb{Z}[1/p])$ where $p$ is prime. Let $i:Y\to X$ be a closed subscheme of pure codimension $r$. Let $n$ be a natural number prime to $p$. Let $\Lambda$ be a finite $\mathbb{Z}/n$-module over $X$. In
Externí odkaz:
http://arxiv.org/abs/2408.02542
Autor:
Nacar, Omer, Koubaa, Anis
This work presents a novel framework for training Arabic nested embedding models through Matryoshka Embedding Learning, leveraging multilingual, Arabic-specific, and English-based models, to highlight the power of nested embeddings models in various
Externí odkaz:
http://arxiv.org/abs/2407.21139
The Internet of Things (IoT) has been introduced as a breakthrough technology that integrates intelligence into everyday objects, enabling high levels of connectivity between them. As the IoT networks grow and expand, they become more susceptible to
Externí odkaz:
http://arxiv.org/abs/2406.02636
The growing interest in satellite imagery has triggered the need for efficient mechanisms to extract valuable information from these vast data sources, providing deeper insights. Even though deep learning has shown significant progress in satellite i
Externí odkaz:
http://arxiv.org/abs/2406.00348
Addressing uncertainty in Deep Learning (DL) is essential, as it enables the development of models that can make reliable predictions and informed decisions in complex, real-world environments where data may be incomplete or ambiguous. This paper int
Externí odkaz:
http://arxiv.org/abs/2405.20230
In this paper we introduce APL (Arabic Programming Language) that uses Large language models (LLM) as semi-compiler to covert Arabic text code to python code then run the code. Designing a full pipeline from the structure of the APL text then a promp
Externí odkaz:
http://arxiv.org/abs/2403.16087
The predominance of English and Latin-based large language models (LLMs) has led to a notable deficit in native Arabic LLMs. This discrepancy is accentuated by the prevalent inclusion of English tokens in existing Arabic models, detracting from their
Externí odkaz:
http://arxiv.org/abs/2402.15313
Autor:
Naimi, Safwen, Koubaa, Olfa, Bouachir, Wassim, Bilodeau, Guillaume-Alexandre, Jeddore, Gregory, Baines, Patricia, Correia, David, Arsenault, Andre
Lichens are symbiotic organisms composed of fungi, algae, and/or cyanobacteria that thrive in a variety of environments. They play important roles in carbon and nitrogen cycling, and contribute directly and indirectly to biodiversity. Ecologists typi
Externí odkaz:
http://arxiv.org/abs/2310.17080