We first learned local image features from image patches in YCbCr space with a sparse autoencoder and then convolved them with large images to obtain global features. Chrominance components were ...

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 ...

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 ...

It's time to upgrade to DDR5. Here's the best RAM for gaming that isn't going to break the bank. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it ...

Deep learning models typically consist of numerous computationally intensive convolutional layers, with the RGB channels contributing to the ... of the kernel size compared to the im2col-based ...

A Java program for compressing and decompressing RGB images using vector quantization, processing each color channel (red, green, blue) separately. Enter the image file name when prompted (e.g., ...

Methods: This study integrates rainfall, surface displacement, and vertical displacement monitoring data, and proposes an automatic failure mode identification method based on deep convolutional ...

We present Diffusion-4K, a novel framework for direct ultra-high-resolution image synthesis using text-to-image diffusion models. The core advancements include: (1) Aesthetic-4K Benchmark: addressing ...

The decoder then recovers the input data from the low-dimensional vectors via transposed convolution. Autoencoder is able to extract local features of images and apply these features to further tasks ...