Zobrazeno 1 - 10
of 62 816
pro vyhledávání: '"Ahsan, A."'
In a controlled cyber-physical network, such as a power grid, any malicious data injection in the sensor measurements can lead to widespread impact due to the actions of the closed-loop controllers. While fast identification of the attack signatures
Externí odkaz:
http://arxiv.org/abs/2408.02011
Autor:
Bappy, Faisal Haque, Hasan, Kamrul, Sajid, Md Sajidul Islam, Pritom, Mir Mehedi Ahsan, Islam, Tariqul
Proof of Stake (PoS) blockchains offer promising alternatives to traditional Proof of Work (PoW) systems, providing scalability and energy efficiency. However, blockchains operate in a decentralized manner and the network is composed of diverse users
Externí odkaz:
http://arxiv.org/abs/2407.20983
Ultrasound Shear Wave Elastography (SWE) is a noteworthy tool for in-vivo noninvasive tissue pathology assessment. State-of-the-art techniques can generate reasonable estimates of tissue elasticity, but high-quality and noise-resiliency in SWE recons
Externí odkaz:
http://arxiv.org/abs/2407.20558
Autor:
Vetter, Dennis, Ahsan, Muhammad, Delicado, Diana, Neubauer, Thomas A., Wilke, Thomas, Roig, Gemma
In this paper, we present our first proposal of a machine learning system for the classification of freshwater snails of the genus Radomaniola. We elaborate on the specific challenges encountered during system design, and how we tackled them; namely
Externí odkaz:
http://arxiv.org/abs/2407.20013
Understanding the dynamics of open quantum systems in strong coupling and non-Markovian regimes remains a formidable theoretical challenge. One popular and well-established method of approximation in these circumstances is provided by the polaron mas
Externí odkaz:
http://arxiv.org/abs/2407.10744
Autor:
Shehzad, Ahsan, Xia, Feng, Abid, Shagufta, Peng, Ciyuan, Yu, Shuo, Zhang, Dongyu, Verspoor, Karin
Graph transformers are a recent advancement in machine learning, offering a new class of neural network models for graph-structured data. The synergy between transformers and graph learning demonstrates strong performance and versatility across vario
Externí odkaz:
http://arxiv.org/abs/2407.09777
Autor:
Mustafa, Muhammad Ahsan, Yaqoot, Yasheerah, Martynov, Mikhail, Karaf, Sausar, Tsetserukou, Dzmitry
This paper discusses developments for a multi-limb morphogenetic UAV, MorphoGear, that is capable of both aerial flight and ground locomotion. A hybrid path planning algorithm based on A* strategy has been developed enabling seamless transition betwe
Externí odkaz:
http://arxiv.org/abs/2407.09625
Autor:
Bappy, Faisal Haque, Zaman, Tarannum Shaila, Sajid, Md Sajidul Islam, Pritom, Mir Mehedi Ahsan, Islam, Tariqul
While blockchains initially gained popularity in the realm of cryptocurrencies, their widespread adoption is expanding beyond conventional applications, driven by the imperative need for enhanced data security. Despite providing a secure network, blo
Externí odkaz:
http://arxiv.org/abs/2407.01426
Anomaly detection and localization in medical imaging remain critical challenges in healthcare. This paper introduces Spatial-MSMA (Multiscale Score Matching Analysis), a novel unsupervised method for anomaly localization in volumetric brain MRIs. Bu
Externí odkaz:
http://arxiv.org/abs/2407.00148
Accurate volumetric image registration is highly relevant for clinical routines and computer-aided medical diagnosis. Recently, researchers have begun to use transformers in learning-based methods for medical image registration, and have achieved rem
Externí odkaz:
http://arxiv.org/abs/2406.09774