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2017-06-12

The dominant sequence transduction models are based on complex recurrent or convolutional neural net… show more
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2018-10-11

We introduce a new language representation model called BERT, which stands for Bidirectional Encoder… show more
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2015-12-08

We present a method for detecting objects in images using a single deep neural network. Our approach… show more
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2015-11-19

In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in co… show more
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2015-12-10

Deeper neural networks are more difficult to train. We present a residual learning framework to ease… show more
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2015-08-26

In fine art, especially painting, humans have mastered the skill to create unique visual experiences… show more
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2015-05-18

There is large consent that successful training of deep networks requires many thousand annotated tr… show more
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2016-12-25
1612.08242 | cs.CV

We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 90… show more
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2015-06-04

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize objec… show more
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2014-09-04
1409.1556 | cs.CV

In this work we investigate the effect of the convolutional network depth on its accuracy in the lar… show more
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2015-11-04
1511.01432 | cs.LG

We present two approaches that use unlabeled data to improve sequence learning with recurrent networ… show more
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2017-08-07

The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN… show more
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2017-12-05

The game of chess is the most widely-studied domain in the history of artificial intelligence. The s… show more
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2016-08-25

Recent work has shown that convolutional networks can be substantially deeper, more accurate, and ef… show more
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2017-03-30

Image-to-image translation is a class of vision and graphics problems where the goal is to learn the… show more
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2016-11-21

We investigate conditional adversarial networks as a general-purpose solution to image-to-image tran… show more
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Highlights - Most important sentences from the article