Zobrazeno 1 - 10
of 110 683
pro vyhledávání: '"A. A. Salah"'
Autor:
Dornier, Hugo, Maître, Olivier P Le, Congedo, Pietro M, Din, Itham Salah El, Marty, Julien, Bourasseau, Sébastien
When numerically solving partial differential equations, for a given problem and operating condition, adaptive mesh refinement (AMR) has proven its efficiency to automatically build a discretization achieving a prescribed accuracy at low cost. Howeve
Externí odkaz:
http://arxiv.org/abs/2412.01274
In this paper, we study an inverse problem of identifying two spatial-temporal source terms in the Schr\"odinger equation with dynamic boundary conditions from the final time overdetermination. We adopt a weak solution approach to solve the inverse s
Externí odkaz:
http://arxiv.org/abs/2410.21123
We present the classification of geodesic completeness on the pseudo-homothetic Lie group of dimension 3. In particular, we exhibit a family of complete metrics such that all geodesics have bounded velocity. As an application, we show that the set of
Externí odkaz:
http://arxiv.org/abs/2410.20612
Dyslexia is one of the most common learning disorders, often characterized by distinct features in handwriting. Early detection is essential for effective intervention. In this paper, we propose an explainable AI (XAI) framework for dyslexia detectio
Externí odkaz:
http://arxiv.org/abs/2410.19821
Thousands of individuals succumb annually to leukemia alone. This study explores the application of image processing and deep learning techniques for detecting Acute Lymphoblastic Leukemia (ALL), a severe form of blood cancer responsible for numerous
Externí odkaz:
http://arxiv.org/abs/2410.10701
Autor:
Mostajeran, Farinaz, Faroughi, Salah A
Multilayer perceptron (MLP) networks are predominantly used to develop data-driven constitutive models for granular materials. They offer a compelling alternative to traditional physics-based constitutive models in predicting nonlinear responses of t
Externí odkaz:
http://arxiv.org/abs/2410.10897
Lymphoma diagnosis, particularly distinguishing between subtypes, is critical for effective treatment but remains challenging due to the subtle morphological differences in histopathological images. This study presents a novel hybrid deep learning fr
Externí odkaz:
http://arxiv.org/abs/2410.06974
Publikováno v:
IEEE ICCA 2024
This paper presents an Arabic Alphabet Sign Language recognition approach, using deep learning methods in conjunction with transfer learning and transformer-based models. We study the performance of the different variants on two publicly available da
Externí odkaz:
http://arxiv.org/abs/2410.00681
Autor:
Lebreton, Jérémy, Brochard, Roland, Ollagnier, Nicolas, Baudry, Matthieu, Salah, Adrien Hadj, Jonniaux, Grégory, Kanani, Keyvan, Goff, Matthieu Le, Masson, Aurore
Autonomous precision navigation to land onto the Moon relies on vision sensors. Computer vision algorithms are designed, trained and tested using synthetic simulations. High quality terrain models have been produced by Moon orbiters developed by seve
Externí odkaz:
http://arxiv.org/abs/2409.11450
Real-time object detection in indoor settings is a challenging area of computer vision, faced with unique obstacles such as variable lighting and complex backgrounds. This field holds significant potential to revolutionize applications like augmented
Externí odkaz:
http://arxiv.org/abs/2409.01871