Abstract: In typical image inpainting tasks, the locations and shapes of damaged or masked areas are often random and irregular. Vanilla convolutions, commonly employed in learning-based inpainting ...

Abstract: Image inpainting is a skill developed to recover the damage part of an images. Many researches states that application wise there are various plausible techniques implemented for an image ...

Rep. Alexandria Ocasio-Cortez’s tough Bronx persona is under fresh scrutiny with a resurfaced childhood nickname from her suburban upstate New York upbringing casting doubt on that publicly portrayed ...

Here’s something fun. Our hacker [Willow Cunningham] has sent us a copy of their homework. This is their final project for the “ECE 574: Cluster Computing” course at the University of Maine, Orono. It ...

Here’s something fun. Our hacker [Willow Cunningham] has sent us a copy of their homework. This is their final project for the “ECE 574: Cluster Computing” course at the University of Maine, Orono. It ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...

Training a Large CNN for Image Classification: Researchers developed a large CNN to classify 1.2 million high-resolution images from the ImageNet LSVRC-2010 contest ...

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 ...