Abstract: Convolutional Neural Networks (CNNs) have achieved remarkable progress in arbitrary artistic style transfer. However, the model size of existing state-of-the-art (SOTA) style transfer ...

Abstract: Knowledge distillation is an effective method for training small and efficient deep learning models. However, the efficacy of a single method can degenerate when transferring to other tasks, ...

Recent advancements in deep learning have significantly improved performance on computer vision tasks. Previous image classification methods primarily modify model architectures or add features, and ...

Quantum distillers Sebastian Ecker and Martin Bohmann prepare the single-copy entanglement experiment, delicately aligning optics used for preparing the photon pairs. Credit: ÖAW/Klaus Pichler Quantum ...

Water purity is essential for various laboratory applications, from analytical testing to pharmaceutical formulations. Among the different water purification methods, distillation remains one of the ...

A number of refineries utilize a combination of technologies to effectively measure and enhance the distillation of crude oil into isolated hydrocarbon components, in order for them to be processed ...