Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

The traditional subspace-based algorithms in the process of coherent direction of arrival (DOA) estimation get in trouble because of the rank loss of the signal covariance matrix. To this end, this ...

A security researcher has discovered a novel security flaw in the Linux kernel using the OpenAI o3 reasoning model. The new vulnerability has been documented under CVE-2025-37899. An official patch ...

Understand the process of convolution and its applications in blurring and sharpening images using two-dimensional filters.

As AI continues to reshape the way developers build applications, Microsoft's Semantic Kernel is emerging as a powerful tool for integrating AI-driven capabilities into existing codebases -- without ...

This use case is a vectorized conv2d kernel. It's lowered from MLIR without using any target-specific dialect (like AIEVec), and it presents a couple of interesting challenges. The first thing that ...

Figure 1. The schematic diagram of STM-ac4C. (A) Feature encoding. One-hot encoding converts the 201 nt RNA sequence into a 5 × 201 matrix. (B) Model architecture. The encoded feature matrix is ...

The convolution kernel is essentially a weight matrix, and the so-called “convolution” operation refers to the matrix multiplication operation. Figure 3 shows the convolution operation with a 3 × 3 ...

Image restoration is actually a deconvolution problem. In the restoration equation, the convolution kernel matrix is a large-scale Toeplitz matrix. In order to reduce the computational complexity of ...