Results 31 to 40 of about 9,502,608 (344)
Communications, 2014 The paper discusses throughput unfairness inherent in the very nature of mixed data rate Wi-Fi networks employing random media access control technique CSMA/CA.
Alaa Mohammed Abdul-Hadi +4 more
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FlowNet: Learning Optical Flow with Convolutional Networks [PDF]
IEEE International Conference on Computer Vision, 2015 Convolutional neural networks (CNNs) have recently been very successful in a variety of computer vision tasks, especially on those linked to recognition. Optical flow estimation has not been among the tasks CNNs succeeded at.
Alexey Dosovitskiy +8 more
semanticscholar +1 more source
Inertial Sensor-Based Robust Gait Analysis in Non-Hospital Settings for Neurological Disorders
Sensors, 2017 The gold standards for gait analysis are instrumented walkways and marker-based motion capture systems, which require costly infrastructure and are only available in hospitals and specialized gait clinics. Even though the completeness and the accuracy of
Can Tunca +5 more
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The SHAPES Smart Mirror Approach for Independent Living, Healthy and Active Ageing
Sensors, 2021 The benefits that technology can provide in terms of health and support for independent living are in many cases not enough to break the barriers that prevent older adults from accepting and embracing technology.
Javier Dorado Chaparro +9 more
doaj +1 more source
EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces [PDF]
Journal of Neural Engineering, 2016 Objective. Brain–computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given BCI
Vernon J. Lawhern +5 more
semanticscholar +1 more source
Efficient Processing of Deep Neural Networks: A Tutorial and Survey [PDF]
Proceedings of the IEEE, 2017 Deep neural networks (DNNs) are currently widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, and robotics.
V. Sze +3 more
semanticscholar +1 more source
Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey [PDF]
Machine Learning and Knowledge Extraction, 2019 Deep Learning is a state-of-the-art technique to make inference on extensive or complex data. As a black box model due to their multilayer nonlinear structure, Deep Neural Networks are often criticized as being non-transparent and their predictions not ...
Vanessa Buhrmester +2 more
semanticscholar +1 more source
Sensors, 2014 Human activity recognition and behavior monitoring in a home setting using wireless sensor networks (WSNs) provide a great potential for ambient assisted living (AAL) applications, ranging from health and wellbeing monitoring to resource consumption ...
Can Tunca +4 more
doaj +1 more source
Telecommunication Economics: Selected Results of the COST Action IS0605 [PDF]
, 2012 Computer Communication Networks; Communications Engineering, Networks; Computers and Society; Management of Computing and Information ...
Stiller, Burkhard +1 more
core +1 more source
Reliability in Computer Networks [PDF]
, 2006 We use a mathematical model of an open queueing network in heavy traffic. The probability limit theorem for the virtual waiting time of a customer in heavy traffic in open queueing networks has been presented. Finally, we present an application of the theorem - a reliability model from computer network practice.
Saulius Minkevicius, Genadijus Kulvietis
openaire +1 more source