Attractor learning with nonlinear, artificial, neural network
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The offshore plant equipment usually has a long life cycle. During its O&M (Operation and Maintenance) phase, since the accidental occurrence of offshore plant equipment causes catastrophic damage, it is necessary to make more efforts for managing critical ...
The two-by-two dot centering model enables predicting the spectral reflectance of color halftones and does not depend on a specific halftoning algorithm. It requires measuring the reflectances of a large number of two-by-two calibration tile patterns. Spec ...
Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2012
The geography of “culture-war” is usually addressed as the expression of religious, socio-economical, ethnically and historical divides that characterise territorial constructs. In recent research trends, psychologists suggest this culture-war divisions re ...
We study the accuracy of channel network extraction methods obtained in two subcatchments of an alpine watershed in Switzerland and compare the results to the ones obtained with the real network, carefully monitored with a high precision DGPS during Summer ...
This paper presents a numerical procedure of material parameter identification for the coupled hydromechanical boundary value problem (BVP) of the self-boring pressuremeter test (SBPT) in clay. First, the neural network (NN) technique is applied to obtain ...
Air pollutants emissions in urban areas are numerous and heterogeneous. Traditional monitoring techniques are restricted to a few highquality instruments missing this spatial heterogeneity. Recently, great interest has been given to low-cost sensors to bet ...
Echo-planar imaging is the dominant functional MRI data acquisition scheme for evaluating the BOLD signal. To date, it remains the only approach providing neurofeedback from spatially localized brain activity. Real-time functional single-voxel proton spect ...
With ever-increasing power densities, Dynamic Thermal Management (DTM) techniques have become mainstream in today’s systems. An important component of such techniques is the thermal trigger. It has been shown that predictive thermal triggers can outperform ...
Convolutional Neural Networks (CNNs) have been widely adopted for many imaging applications. For image aesthetics prediction, state-of-the-art algorithms train CNNs on a recently-published large-scale dataset, AVA. However, the distribution of the aestheti ...
Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from image to 3D pose, which ignores the dependencies between human joints, or model these dependencies via a ...