Machine Learning

A SAR ship dataset for detection, discrimination and analysis


Synthetic Aperture Radar is a monitoring solution which is especially well fitted to maritime surveillance. The large swath widths, time-independent, weather resistant observations can be very useful for the detection of ships typically invisible to other forms of monitoring. A dataset which contains 43 Sentinel-1 Extended Wide Swath images and 3 RADARSAT-2 ScanSAR Narrow images between the 6th October 2014 to the 22 July 2015 is described and presented here.

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Dataset Details

Citation Author(s):
Submitted by:
Colin Schwegmann
Last updated:
Mon, 10/16/2017 - 09:38
DOI:
10.21227/H2RK82
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[1] , "A SAR ship dataset for detection, discrimination and analysis", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2RK82. Accessed: Oct. 23, 2017.
@data{h2rk82-17,
doi = {10.21227/H2RK82},
url = {http://dx.doi.org/10.21227/H2RK82},
author = { },
publisher = {IEEE Dataport},
title = {A SAR ship dataset for detection, discrimination and analysis},
year = {2017} }
TY - DATA
T1 - A SAR ship dataset for detection, discrimination and analysis
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2RK82
ER -
. (2017). A SAR ship dataset for detection, discrimination and analysis. IEEE Dataport. http://dx.doi.org/10.21227/H2RK82
, 2017. A SAR ship dataset for detection, discrimination and analysis. Available at: http://dx.doi.org/10.21227/H2RK82.
. (2017). "A SAR ship dataset for detection, discrimination and analysis." Web.
1. . A SAR ship dataset for detection, discrimination and analysis [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2RK82
. "A SAR ship dataset for detection, discrimination and analysis." doi: 10.21227/H2RK82

Dataset malware/beningn permissions Android


This dataset is a result of my research production into machine learning in android security. The data was obtained by a process that consisted to map a binary vector of permissions used for each application analyzed {1=used, 0=no used}. Moreover, the samples of malware/benign were devided by "Type"; 1 malware and 0 non-malware.

When I did my research, the datasets of malware and benign Android applications were not available, then I give to the community a part of my research results for the future works.

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Dataset Details

Citation Author(s):
Submitted by:
Christian Urcuqui
Last updated:
Thu, 11/17/2016 - 10:43
DOI:
10.21227/H26P4M
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[1] , "Dataset malware/beningn permissions Android", IEEE Dataport, 2016. [Online]. Available: http://dx.doi.org/10.21227/H26P4M. Accessed: Oct. 23, 2017.
@data{h26p4m-16,
doi = {10.21227/H26P4M},
url = {http://dx.doi.org/10.21227/H26P4M},
author = { },
publisher = {IEEE Dataport},
title = {Dataset malware/beningn permissions Android},
year = {2016} }
TY - DATA
T1 - Dataset malware/beningn permissions Android
AU -
PY - 2016
PB - IEEE Dataport
UR - 10.21227/H26P4M
ER -
. (2016). Dataset malware/beningn permissions Android. IEEE Dataport. http://dx.doi.org/10.21227/H26P4M
, 2016. Dataset malware/beningn permissions Android. Available at: http://dx.doi.org/10.21227/H26P4M.
. (2016). "Dataset malware/beningn permissions Android." Web.
1. . Dataset malware/beningn permissions Android [Internet]. IEEE Dataport; 2016. Available from : http://dx.doi.org/10.21227/H26P4M
. "Dataset malware/beningn permissions Android." doi: 10.21227/H26P4M