You will be redirected to our submission process. Lipid nanoparticles (LNPs) have been one of the most clinically verified platforms for drug and nucleic acid delivery, and their essential roles have ...
The team built a DenseNet – a densely connected convolutional neural network – that learns hierarchical features directly ...
RNA is the means of translating the genetic code embedded in DNA into proteins, which serve as enzymes, transporters, ...
A team at UCSF developed a multitask deep learning framework that can effectively predict Alzheimer’s disease diagnosis, cognitive scores, and future cognitive decline using only baseline MRI and ...
Abstract: Clustering is a fundamental task in machine learning and data mining. The success of deep learning, especially deep generative models, has given birth to the next generation of clustering - ...
Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
ABSTRACT: The rapid growth of technology impacts all aspects of modern life, including banking and financial transactions. While these industries benefit significantly from technological advancements, ...
Abstract: Deep learning has achieved outstanding success in the hyperspectral image (HSI) classification task. Almost all the current deep learning methods are used to conduct classification ...
CAD-DR is a deep learning-based system for dimensionality reduction of 3D CAD models using a 3D convolutional autoencoder. The system supports full STL to voxel transformation, encoding, ...
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