Offical implementation of "Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection" we also add our config in https://github.com/zcablii/LSKNet and ...

In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...

Guillermo Del Toro’s Frankenstein is now out on Netflix, with the monster (played by Jacob Elordi) shown to be far more human than his titular creator. The ending of the Netflix film differs from both ...

Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...

In this video, we will understand what is Convolution Operation in CNN. Convolution Operation is the heart of Convolutional Neural Network. It is responsible for detecting the edges or features of the ...

Weapons is a layered story told through different character perspectives, with a compelling metaphor at the heart of the film. In the very first scene, Weapons jumps right into its terrible ...

Abstract: Dilated convolution is a powerful technique for expanding the receptive field without increasing the convolution kernel size, making it highly valuable in image segmentation tasks. However, ...