Name
Abstract | ||
|---|---|---|
The performance of object recognition and classification on remote sensing imagery is highly dependent on the quality of extracted features, amount of labelled data and the priors defined for contextual models. In this study, we examine the representation learning opportunities for remote sensing. First we attacked localization of contextual cues for complex object detection using disentangling factors learnt from a small amount of labelled data. The complex object, which consists of several sub-parts is further represented under the Conditional Markov Random Fields framework. As a second task, end-to-end target detection using convolutional sparse auto-encoders (CSA) using large amount of unlabelled data is analysed. Proposed methodologies are tested on complex airfield detection problem using Conditional Random Fields and recognition of dispersal areas, park areas, taxi routes, airplanes using CSA. The method is also tested on the detection of the dry docks in harbours. Performance of the proposed method is compared with standard feature engineering methods and found competitive with currently used rule-based and supervised methods. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICPR.2014.637 | Pattern Recognition |
Keywords | DocType | ISSN |
Markov processes,feature extraction,geophysical image processing,image classification,object detection,object recognition,random processes,remote sensing,CSA,airplane recognition,complex airfield detection problem,conditional Markov random fields framework,conditional random fields,contextual cue localization,contextual models,contextual object,convolutional sparse auto-encoders,disentangling factors,dispersal area recognition,dry dock detection,end-to-end target detection,feature extraction,harbours,object classification,object detection,object recognition,park area recognition,region detection,remote sensing imagery,representation learning opportunities,taxi route recognition | Conference | 1051-4651 |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Orhan Firat | 1 | 281 | 29.13 |
| Gulcan Can | 2 | 20 | 4.28 |
| Yarman Vural, F.T. | 3 | 73 | 6.17 |