Graph neural networks (GNNs) have been applied with great success across science and engineering, but we do not understand why they work so well. Motivated by ...

Input: "A beautiful girl on a boat"; Resolution: 2048 x 1152. Input: "Miniature house with plants in the potted area, hyper realism, dramatic ambient lighting, high detail"; Resolution: 4096 x 4096.

This wiki describes how to work with object detection models trained using TensorFlow Object Detection API. OpenCV 3.4.1 or higher is required. Deep learning networks in TensorFlow are represented as ...

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

In seismic exploration, dense and evenly spatial sampled seismic traces are crucial for successful implementation of most seismic data processing and interpretation algorithms. Recently, numerous ...

Abstract: Change detection (CD) is an important task in remote sensing image processing. The main research goal is to identify whether the target area has changed. Recently, the rise of deep learning ...

College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China ...

Three-dimensional (3D) liver tumor segmentation from Computed Tomography (CT) images is a prerequisite for computer-aided diagnosis, treatment planning, and monitoring of liver cancer. Despite many ...