Researchers look to deep learning techniques in order to streamline the time-consuming process of identifying 2D materials ... Convolutional Neural Network (CNN), the research team achieved ...

To tackle this problem, scientists conducted a large multi-center study involving 13 hospitals in China to train deep learning ... different CNN models. The first model only used 2D ultrasound ...

Transfer learning is an efficient approach for using information from large well annotated datasets (such as ImageNet) for CADe problems. “Off-the-shelf” features from deep CNN models can be applied ...

“[Our] research builds on recent advances in using deep learning to predict and localize ... Above: Mesh R-CNN converts 2D objects to 3D shapes. Facebook researchers say they augmented the ...

One of the key components of most deep learning–based computer vision applications is the convolutional neural network (CNN). Invented in the 1980s by deep learning pioneer Yann LeCun ...

“Deep learning methods are, let’s say, very slow learners,” Cohen said. This poses few problems if you’re training a CNN to recognize ... anywhere in the 2D plane and is able to recognize ...

Researchers have developed a deep learning-based approach that significantly streamlines the accurate identification and ...