Researchers have developed an AI image generator that produces images in just four steps, rather than dozens. This could bring fast, private image generation directly to consumer devices. When you ...

"An Adaptive and Scalable Convolution Framework for Low-Light Image Enhancement via Analytic Functions Subordinate to Laguerre Polynomials" The proposed method leverages coefficient bounds derived ...

The previous deep CNN-based single-image dehazing methods are devoted to improving the performance by increasing the network’s depth and width. In this paper, a novel Large Kernel Convolution Dehaze ...

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...

The threat actor uses a signed driver file containing two user-mode shellcodes to execute its ToneShell backdoor. The Chinese espionage-focused APT Mustang Panda has been using a kernel-mode rootkit ...

Abstract: Polyp image segmentation, as one of the important components of medical image processing tasks, provides a powerful auxiliary role for clinical colonoscopy. However, it is very difficult to ...

Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...

🖼️ Parallel Image Convolution, applying a blur filter to images. Written in C, optimized in three different ways: MPI, MPI & OpenMP and CUDA.