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pro vyhledávání: '"Hamila A"'
Autor:
Adalioglu, Ilke, Kiranyaz, Serkan, Ahishali, Mete, Degerli, Aysen, Hamid, Tahir, Ghaffar, Rahmat, Hamila, Ridha, Gabbouj, Moncef
Echocardiography is the most widely used imaging to monitor cardiac functions, serving as the first line in early detection of myocardial ischemia and infarction. However, echocardiography often suffers from several artifacts including sensor noise,
Externí odkaz:
http://arxiv.org/abs/2412.06445
The success of modern deep learning is attributed to two key elements: huge amounts of training data and large model sizes. Where a vast amount of data allows the model to learn more features, the large model architecture boosts the learning capabili
Externí odkaz:
http://arxiv.org/abs/2410.03790
The advent of Intelligent Reflecting Surfaces (IRS) and Unmanned Aerial Vehicles (UAVs) is setting a new benchmark in the field of wireless communications. IRS, with their groundbreaking ability to manipulate electromagnetic waves, have opened avenue
Externí odkaz:
http://arxiv.org/abs/2407.01576
Federated Learning (FL) is a rapidly growing field in machine learning that allows data to be trained across multiple decentralized devices. The selection of clients to participate in the training process is a critical factor for the performance of t
Externí odkaz:
http://arxiv.org/abs/2311.06801
Visual crowd counting estimates the density of the crowd using deep learning models such as convolution neural networks (CNNs). The performance of the model heavily relies on the quality of the training data that constitutes crowd images. In harsh we
Externí odkaz:
http://arxiv.org/abs/2310.07245
Over the last decade, there has been a remarkable surge in interest in automated crowd monitoring within the computer vision community. Modern deep-learning approaches have made it possible to develop fully-automated vision-based crowd-monitoring app
Externí odkaz:
http://arxiv.org/abs/2308.10677
Autor:
Hamila, Oumaima, Henry, Christopher J., Molina, Oscar I., Bidinosti, Christopher P., Henriquez, Maria Antonia
Fusarium head blight (FHB) is one of the most significant diseases affecting wheat and other small grain cereals worldwide. The development of resistant varieties requires the laborious task of field and greenhouse phenotyping. The applications consi
Externí odkaz:
http://arxiv.org/abs/2303.05634
Automatic crowd counting using density estimation has gained significant attention in computer vision research. As a result, a large number of crowd counting and density estimation models using convolution neural networks (CNN) have been published in
Externí odkaz:
http://arxiv.org/abs/2302.05374
Publikováno v:
European Journal of Case Reports in Internal Medicine (2024)
Introduction: Castleman disease (CD) is a rare lymphoproliferative disorder having a variegated clinical presentation. Diagnosis of the idiopathic HIV- and HHV8-negative multicentric CD (iMCD) subtype poses a challenge given its non-specific clinical
Externí odkaz:
https://doaj.org/article/72814000926b4d17a4595542ff436be3
Deep learning models require an enormous amount of data for training. However, recently there is a shift in machine learning from model-centric to data-centric approaches. In data-centric approaches, the focus is to refine and improve the quality of
Externí odkaz:
http://arxiv.org/abs/2212.01452