A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.

Abstract: We propose a novel spatiotemporal fusion method based on deep convolutional neural networks (CNNs) under the application background of massive remote sensing data. In the training stage, we ...

Researchers from Science Tokyo develop a Multi-scale Hessian-enhanced Patch-based Neural Network Model for Segmentation of Liver Tumor from CT Scans. Liver cancer is the sixth most common cancer ...

Deep learning is an effective and useful technique that has been widely applied in a variety of fields, including computer vision, machine vision, and natural language processing. Deepfakes uses deep ...

High-quality and high-resolution precipitation products are critically important to many hydrological applications. Advances in satellite remote sensing instruments and data retrieval algorithms ...

Abstract: We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented ...

In space exploration, there is the Google Lunar X Prize for placing a rover on the lunar surface. In medicine, there is the Qualcomm Tricorder X Prize for developing a Star Trek-like device for ...