6 accepted papers
Spatial transcriptomics (ST) has emerged as a revolutionary approach in the field of tissue analysis that can offer spatial resolved molecular insights for the identification of anomalous regions (AR) on human cancers. Current ST-based methods for detecting AR focus narrowly on the molecular feature
Geomagnetic map interpolation aims to infer unobserved geomagnetic data at spatial points, yielding critical applications in navigation and resource exploration. However, existing methods for scattered data interpolation are not specifically designed for geomagnetic maps, which inevitably leads to s…
The rapid development of spatial transcriptomics (ST) allows researchers to measure the spatial-level gene expression in tissues. Although powerful, the cost for collecting the ST data is expensive, and thus several studies aim to predict gene expression in ST by utilizing their corresponding H/E st…
Sampling-based path planning algorithms, such as Rapidly-exploring Random Tree (RRT), are widely used for motion planning in high degree-of-freedom robotic systems due to their efficiency in exploring high-dimensional spaces. However, traditional methods rely on binary collision detection, which onl
In the multimodal (text, audio, and visual) sentiment analysis, the current methods generally consider the bi-modal sentiment interaction, resulting in inadequate mining and fusion of relations between modalities. In this paper, we propose the concept of multimodal 3D (3-Dimensional) stereoscopic at…
Many soft robots are made of hyperelastic silicone rubbers and usually experience large nonlinear deformations in actions. Accurate material parameters are essential to provide reliable analysis and support robot designs. This letter presents a practical material parameter determination method by it