Multiple String Matching on a GPU using CUDAs
C. Kouzinopoulos +2 more
openalex +2 more sources
MFR‐UNet: A Medical Image Segmentation Network With Fused Multi‐Scale Feature Refinement
Addressing the challenges of CNN‐based methods (especially U‐Net and its variants) in medical image segmentation—such as difficulties in capturing long‐range dependencies and insufficient refinement of multi‐scale features—this paper proposes the MFR‐UNet architecture integrated with a multi‐scale feature refinement mechanism, which enhances ...
Shaoqiang Wang +7 more
wiley +1 more source
Trends and Incidence of Hearing Implant Utilization in Italy: A Population-Based Study. [PDF]
Ciminello E +10 more
europepmc +1 more source
Parallel acceleration algorithm for wavelet denoising of UAVAGS data based on CUDA
Hexi Wu +7 more
openalex +1 more source
Leopard‐EM: an extensible 2D template‐matching package to accelerate in situ structural biology
In situ cryo‐EM coupled with 2D template matching (2DTM) holds the potential to visualize the cellular structureome in context, but further developments are required to make this a reality. We describe Leopard‐EM (Location and orientation of particles found using two‐dimensional tEmplate Matching), an extensible Python package for 2DTM to accelerate in
Matthew D. Giammar +3 more
wiley +1 more source
Large-scale acceleration algorithms for a deep convective physical parameterization scheme on GPU. [PDF]
Wang Y +6 more
europepmc +1 more source
UAV‐based remote sensing of bee nesting aggregations with computer vision for object detection
Our novel application of UAV imagery and object detection models for mapping and censusing ground nesting bee aggregations represents a rapid, cost‐effective solution for overcoming limitations in traditional manual methods. This workflow has applications for bee conservation, management and research such as monitoring bee nesting populations before ...
Tobias G. Mueller, Mark A. Buckner
wiley +1 more source
ARTreeFormer: A faster attention-based autoregressive model for phylogenetic inference. [PDF]
Xie T, Mao Y, Zhang C.
europepmc +1 more source
The CUDA implementation of the method of lines for the curvature dependent flows
Tomáš Oberhuber +2 more
openalex +1 more source

