The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from various sources and setups.
Convolutional neural network (CNN) is a neural network that can make use of the internal structure of data such as the 2D structure of image data.
#9 best model for Sentiment Analysis on IMDb
We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks.
I present a new way to parallelize the training of convolutional neural networks across multiple GPUs.
This means that the super-resolution (SR) operation is performed in HR space.
We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e. g., 10-150 MFLOPs).
#100 best model for Image Classification on ImageNet
Convolutional Neural Networks (CNNs) have recently achieved remarkably strong performance on the practically important task of sentence classification (kim 2014, kalchbrenner 2014, johnson 2014).
We propose DoReFa-Net, a method to train convolutional neural networks that have low bitwidth weights and activations using low bitwidth parameter gradients.