Name
Abstract | ||
|---|---|---|
This paper deals with the field of computer vision, mainly for the application of deep learning in object detection task. On the one hand, there is a simple summary of the datasets and deep learning algorithms commonly used in computer vision. On the other hand, a new dataset is built according to those commonly used datasets, and choose one of the network called faster r-cnn to work on this new dataset. Through the experiment to strengthen the understanding of these networks, and through the analysis of the results learn the importance of deep learning technology, and the importance of the dataset for deep learning. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 16TH IEEE/ACIS INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE (ICIS 2017) | deep learning, neural network, faster r-cnn, dataset |
Field | DocType | Citations |
Robot learning,Online machine learning,Competitive learning,Semi-supervised learning,Active learning (machine learning),Computer science,Deep belief network,Unsupervised learning,Artificial intelligence,Deep learning,Machine learning | Conference | 2 |
PageRank | References | Authors |
0.36 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinyi Zhou | 1 | 68 | 5.53 |
| Wei Gong | 2 | 104 | 32.67 |
| Wenlong Fu | 3 | 110 | 13.14 |
| Fengtong Du | 4 | 2 | 1.38 |