Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Hamila, Ridha"'
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
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
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
Density estimation is one of the most widely used methods for crowd counting in which a deep learning model learns from head-annotated crowd images to estimate crowd density in unseen images. Typically, the learning performance of the model is highly
Externí odkaz:
http://arxiv.org/abs/2212.01450
The rapid outbreak of COVID-19 pandemic invoked scientists and researchers to prepare the world for future disasters. During the pandemic, global authorities on healthcare urged the importance of disinfection of objects and surfaces. To implement eff
Externí odkaz:
http://arxiv.org/abs/2212.01445
Video surveillance using drones is both convenient and efficient due to the ease of deployment and unobstructed movement of drones in many scenarios. An interesting application of drone-based video surveillance is to estimate crowd densities (both pe
Externí odkaz:
http://arxiv.org/abs/2211.07137