Back to knowledge graph
science
machine-learning
Confidence 75%

Deep Residual Learning for Image Recognition: A Survey

Deep Residual Learning for Image Recognition: A Survey Deep Residual Networks have recently been shown to significantly improve the performance of neural networks trained on ImageNet, with results beating all previous methods on this dataset by large margins in the image classification task. However, the meaning of these impressive numbers and their implications for future research are not fully understood yet. In this survey, we will try to explain what Deep Residual Networks are, how they ach...

Anonymous preview shows an excerpt only. Sign in to read the full item.

Cited 1000 times
Deep Residual Learning for Image Recognition: A Survey | Awareness Public Knowledge