Classification of crystallization outcomes using deep convolutional neural networks

27 Mar 20182 code implementations

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.

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

17 Apr 201760 code implementations

We present a class of efficient models called MobileNets for mobile and embedded vision applications.

IMAGE CLASSIFICATION OBJECT DETECTION

Effective Use of Word Order for Text Categorization with Convolutional Neural Networks

HLT 2015 2 code implementations

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.

SENTIMENT ANALYSIS

Convolutional Neural Networks for Sentence Classification

EMNLP 2014 64 code implementations

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.

SENTENCE CLASSIFICATION SENTIMENT ANALYSIS

One weird trick for parallelizing convolutional neural networks

23 Apr 20143 code implementations

I present a new way to parallelize the training of convolutional neural networks across multiple GPUs.

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

CVPR 2018 10 code implementations

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).

IMAGE CLASSIFICATION OBJECT DETECTION

A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

IJCNLP 2017 18 code implementations

Convolutional Neural Networks (CNNs) have recently achieved remarkably strong performance on the practically important task of sentence classification (kim 2014, kalchbrenner 2014, johnson 2014).

REGRESSION SENTENCE CLASSIFICATION

Fast Algorithms for Convolutional Neural Networks

CVPR 2016 2 code implementations

The algorithms compute minimal complexity convolution over small tiles, which makes them fast with small filters and small batch sizes.

PEDESTRIAN DETECTION SELF-DRIVING CARS

DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

20 Jun 20169 code implementations

We propose DoReFa-Net, a method to train convolutional neural networks that have low bitwidth weights and activations using low bitwidth parameter gradients.