All-component 3D-printed lithium-ion batteries are fabricated by printing graphene-oxide-based
composite inks and solid-state gel polymer electrolyte. An entirely 3D-printed full cell …

Convolutional neural networks (CNNs) have achieved great success on grid-like data such
as images, but face tremendous challenges in learning from more generic data such as …

… Zhengyang Wang is with the Department of Computer Science and Engineering, Texas
A&M … Meng Liu and Zhengyang Wang contribute equally to this work, and their names are in …

Deep models trained in supervised mode have achieved remarkable success on a variety
of tasks. When labeled samples are limited, self-supervised learning (SSL) is emerging as a …

Dilated convolutions, also known as atrous convolutions, have been widely explored in deep
convolutional neural networks (DCNNs) for various tasks like semantic image segmentation…

Transient technology is an emerging field that requires materials, devices, and systems to
be capable of disappearing with minimal or non-traceable remains over a period of stable …

Augmented reality (AR) displays, as the next generation platform for spatial computing and
digital twins, enable users to view digital images superimposed on real-world environment, …

Modeling customer shopping intentions is a crucial task for e-commerce, as it directly impacts
user experience and engagement. Thus, accurately understanding customer preferences …

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus
of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI …

Deep learning has shown its great promise in various biomedical image segmentation tasks.
Existing models are typically based on U-Net and rely on an encoder-decoder architecture …