DEMO: Dielectric elastomer actuators (DEAs) for the restoration of facial movements

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In two-stage solid-state transformers (SSTs) equipped with LLC DC/DC converters for galvanic isolation, fixed-frequency open-loop operation of LLC stages has been a straightforward and prevailing design choice. Meanwhile, with a closed-loop-operated LLC co ...

Understanding the concept of dynamic aperture provides essential insights into nonlinear beam dynamics, beam losses, and the beam lifetime in circular particle accelerators. This comprehension is crucial for the functioning of modern hadron synchrotrons li ...

Deploying compute-intensive deep neural networks (DNNs) on resource-constrained end devices has become a prominent trend, enabling localized intelligence. However, efficiently deploying these DNNs at scale poses challenges. To address this, extensive resea ...

Species distribution models (SDMs) aim to predict the distribution of species by relating occurrence data with environmental variables. Recent applications of deep learning to SDMs have enabled new avenues, specifically the inclusion of spatial data (envir ...

This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

Background: 3D reconstruction of Wilms’ tumor provides several advantages but are not systematically performed because manual segmentation is extremely time-consuming. The objective of our study was to develop an artificial intelligence tool to automate th ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

DEMO: Dielectric elastomer actuators (DEAs) for the restoration of facial movements

Chat with Graph Search

Design Trade-offs of Second Harmonic Minimization in Solid-State Transformers

Assessing the Performance of Deep Learning Predictions for Dynamic Aperture of a Hadron Circular Particle Accelerator

RAPNet: Resolution-Adaptive and Predictive Early Exit Network for Efficient Image Recognition

Multi-Scale and Multimodal Species Distribution Modeling

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (1/6)

Automation of Wilms’ tumor segmentation by artificial intelligence

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life