Name
Title | ||
|---|---|---|
Learning and Transferring Convolutional Neural Network Knowledge to Ocean Front Recognition |
Abstract | ||
|---|---|---|
In this letter, we investigated how to apply a deep learning method, in particular convolutional neural networks (CNNs), to an ocean front recognition task. Exploring deep CNNs knowledge to ocean front recognition is a challenging task, because the training data is very scarce. This letter overcomes this challenge using a sequence of transfer learning steps via fine-tuning. The core idea is to ext... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LGRS.2016.2643000 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Oceans,Feature extraction,Computer architecture,Machine learning,Training data,Neural networks,Data mining | Data set,Computer science,Convolutional neural network,Remote sensing,Transfer of learning,Artificial intelligence,Deep learning,Artificial neural network,Deep knowledge,Training set,Computer vision,Feature extraction,Machine learning | Journal |
Volume | Issue | ISSN |
14 | 3 | 1545-598X |
Citations | PageRank | References |
4 | 0.43 | 10 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Estanislau Lima | 1 | 12 | 1.65 |
| Xin Sun | 2 | 51 | 10.45 |
| Junyu Dong | 3 | 99 | 23.43 |
| Hui Wang | 4 | 291 | 85.17 |
| Yuting Yang | 5 | 44 | 10.79 |
| Lipeng Liu | 6 | 9 | 1.21 |