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 ...

Generating molecular structures with certain desired properties is a fundamental problem for material science research. Deep learning models have demonstrated big potential to identify novel materials ...

Posted in Microcontrollers, Raspberry Pi Tagged cluster, image convolution, parallel processing, Raspberry Pi Pico ← An Open-Source Wii U Gamepad An Awful 1990s PDA Delivers AI Wisdom → ...

OpenAI says ‘our GPUs are melting’ as it limits ChatGPT image generation requests The company is trying to make image generation more efficient, according to CEO Sam Altman.

IGConv: Implicit Grid Convolution for Multi-Scale Image Super-Resolution For Image Super-Resolution (SR), it is common to train and evaluate scale-specific models composed of an encoder and upsampler ...

This project involves performing a valid convolution on a 300x300 image using a 5x5 kernel (stride 1) with multithreading. The goal is to efficiently apply the convolution filter using multiple ...

In this article, a multihop graph rectifies attention and spectral overlap grouping convolutional fusion network (MRSGFN) for HSI classification is proposed. In the graph convolution branch, a ...

Currently, the improvement in the processing capacity of traditional processors considerably lags behind the demands of real-time image processing caused by the advancement of photodetectors and the ...