Abstract: This paper proposes a direct model for conditional probability density forecasting of residential loads, based on a deep mixture network. Probabilistic residential load forecasting can ...
You are not limited to the LOL dataset. You can place any images in source/low/. The algorithm will process whatever files it finds there: Why 64? 64 = 128/2: one exposure stop below the perceptually ...
ABSTRACT: The Voigt function is the convolution of a Lorentzian and a Guaussian density. The computation of these functions is required in several problems arising in a variety of physicochemical ...
College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China ...
Three-dimensional (3D) liver tumor segmentation from Computed Tomography (CT) images is a prerequisite for computer-aided diagnosis, treatment planning, and monitoring of liver cancer. Despite many ...
The memristor-based convolutional neural network (CNN) gives full play to the advantages of memristive devices, such as low power consumption, high integration density, and strong network recognition ...
Protein structure prediction is a longstanding challenge in computational biology. Through extension of deep learning-based prediction to interresidue orientations in addition to distances, and the ...
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