Evidence map›Paper›PMID 24427198›Full record

ArticleCognitive neurodynamics2013

Airport detection in remote sensing images: a method based on saliency map.

Xin Wang, Qi Lv, Bin Wang, Liming Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cognitive neurodynamics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xin WangDepartment of Electronic Engineering, Fudan University, Shanghai, 200433 China.
Qi LvDepartment of Electronic Engineering, Fudan University, Shanghai, 200433 China.
Bin WangDepartment of Electronic Engineering, Fudan University, Shanghai, 200433 China ; The Key Laboratory of Wave Scattering and Remote Sensing Information, Fudan University, Shanghai, 200433 China.
Liming ZhangDepartment of Electronic Engineering, Fudan University, Shanghai, 200433 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection of airport attracts lots of attention and becomes a hot topic recently because of its applications and importance in military and civil aviation fields. However, the complicated background around airports brings much difficulty into the detection. This paper presents a new method for airport detection in remote sensing images. Distinct from other methods which analyze images pixel by pixel, we introduce visual attention mechanism into detection of airport and improve the efficiency of detection greatly. Firstly, Hough transform is used to judge whether an airport exists in an image. Then an improved graph-based visual saliency model is applied to compute the saliency map and extract regions of interest (ROIs). The airport target is finally detected according to the scale-invariant feature transform features which are extracted from each ROI and classified by hierarchical discriminant regression tree. Experimental results show that the proposed method is faster and more accurate than existing methods, and has lower false alarm rate and better anti-noise performance simultaneously.

Indexed as

Airport detectionHierarchical discriminant regression (HDR) treeHough transformSaliency mapScale-invariant feature transform (SIFT)Visual attention

Identifiers

PMID24427198
PMCPMC3595433

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.