Explore the latest peer-reviewed research with AI-generated summaries, key findings, and insights for easy understanding. All content is legally sourced from academic metadata with links to original papers.
We introduce a method to render Neural Radiance Fields (NeRFs) in real time using PlenOctrees, an octree-based 3D representation which supports view-dependent effects. Our real-time neural rendering a...
Artificial intelligence (AI) has an astonishing potential in assisting clinical decision making and revolutionizing the field of health care. If the training data is misrepresentative of the populatio...
Within Convolutional Neural Network (CNN), the convolution operations are good at extracting local features but experience difficulty to capture global representations. On MSCOCO, it outperforms ResNe...
We present MVSNeRF, a novel neural rendering approach that can efficiently reconstruct neural radiance fields for view synthesis. Our approach can generalize across scenes (even indoor scenes, complet...
Coarse-to-fine strategies have been extensively used for the architecture design of single image deblurring networks. Extensive experiments on the GoPro and RealBlur datasets demonstrate that the prop...
It is very challenging for various visual tasks such as image fusion, pedestrian detection and image-to-image translation in low light conditions due to the loss of effective target areas. We believe...
Multi-modal reasoning systems rely on a pre-trained object detector to extract regions of interest from the image. Our approach can be easily extended for visual question answering, achieving competit...
Transformer architectures have become the model of choice in natural language processing and are now being introduced into computer vision tasks such as image classification, object detection, and sem...
Monocular 3D object detection is an important task for autonomous driving considering its advantage of low cost. Our solution achieves 1st place out of all the vision-only methods in the nuScenes 3D d...
Self-supervised pretraining followed by supervised fine-tuning has seen success in image recognition, especially when labeled examples are scarce, but has received limited attention in medical image a...
Genomics research has improved our understanding of the genetic basis for human traits and diseases. Here, we review the current disparities in cardiovascular genomics research, and we outline how the...
Neurons that express a specific molecular marker are activated by ‘electroacupuncture’ stimulation.
The UK Medical Research Council’s widely used guidance for developing and evaluating complex interventions has been replaced by a new framework, commissioned jointly by the Medical Research Council an...
Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Most notably, eggNOG-mapper v2 now...
This research explores Differential abundance testing on single-cell data using k-n..., contributing new insights to the field of Artificial Intelligence.
This research explores Battery thermal management systems (BTMs) based on phase cha..., contributing new insights to the field of Physics & Space Science.
Electrostatic energy storage technology based on dielectrics is fundamental to advanced electronics and high-power electrical systems. We achieve an ultrahigh energy density of 152 joules per cubic ce...
This research explores Amplifying STING activation by cyclic dinucleotide–manganese..., contributing new insights to the field of Physics & Space Science.
Deep generative models are a class of techniques that train deep neural networks to model the distribution of training samples. In particular, this compendium covers energy-based models, variational a...
Molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area is one of the most popular methods to estimate binding free energies. Multiple illustrating examples can be accessed through gmx_M...