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黎强
2017-06-10 20:15:04 +08:00
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@@ -3,5 +3,5 @@ keras implementation of [A simple neural network module for relational reasonin
Relation network is a noval neural network introduced by deepmind in [A simple neural network module for relational reasoning](https://arxiv.org/pdf/1706.01427.pdf). It can achieve super-human performance in challenging visual question answering datasets such as CLEVR.
I implement Relation network using keras and train it on a challenging visual question answering dataset called [Cornell NLVR](https://github.com/cornell-lic/nlvr). The training is in progress. The temporal test accuracy is 76.87%, which is much higher than the previous state of the art (61.99%).
I implement Relation network using keras and train it on a challenging visual question answering dataset called [Cornell NLVR](https://github.com/cornell-lic/nlvr). The training is in progress. The temporal test accuracy is 98.10%, which is much higher than the previous state of the art (61.99%).