M[Formula: see text]DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson's disease(PD) progression using whole-blood RNA sequencing data. [PDF]
Wei Z, Zeqi X, Chenjun W, Qi D.
europepmc +1 more source
Real‐time by‐example texture synthesis and filtering using local statistics exchange
Abstract Real‐time by‐example texture synthesis is used in interactive virtual worlds to generate the appearance of an unbounded surface from an exemplar texture with as few repetitions as possible. Currently, leading real‐time methods rely on a tiling and blending scheme which is known to synthesize well texture patterns with little spatial ...
Nicolas Lutz, Guillaume Gilet
wiley +1 more source
Abstract Correlation‐based rendering techniques continue to advance, and efficiently exploiting correlations between pixel estimates has become increasingly important. The deep combiner framework [BHHM20] allows us to fuse independent and correlated pixel estimates but focuses solely on spatial correlations.
W. Zhou, E. Hughes, T. Hachisuka
wiley +1 more source
Multi-scale fusion convolution network with progressive dilation for real-time salient object detection of surface defects on strip steel. [PDF]
Zhang Z, Zou Y, Liu X, Zhang X.
europepmc +1 more source
Hybrid CNN-transformer demosaicing for bioinspired single-chip color-near-infrared fluorescence imaging in oncologic surgery. [PDF]
Jin Y +8 more
europepmc +1 more source
Authoring Terrestrial Planets with Diffusion Models
Abstract To support the design and subsequent generation of terrestrial planets for use in the creative media, we propose a solution that employs a generative model trained on satellite data from planetary bodies with a defined solid surface, such as the Earth and Mars.
Oliver Borg +6 more
wiley +1 more source
Wave modelling of 3 + 1 dimensional Wazwaz Kaur Boussinesq equation with the bilinear neural network method. [PDF]
Shahen NHM +4 more
europepmc +1 more source
Tubes or Ribbons? Comparing Texture‐space Visualization for Multivariate Line Data
Abstract Multivariate line data is critical for analyzing flow fields, agent systems, and dynamic trajectories. Embedding secondary variables along spatial paths using surface‐based primitives such as ribbons and circular tubes introduces challenges related to perspective, scale, and distortion.
B. Russig +3 more
wiley +1 more source
BiToxNet: a deep learning framework integrating multimodal features for accurate identification of neurotoxic peptides and proteins. [PDF]
Wang F +9 more
europepmc +1 more source

