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## GMTI.md

      
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                Ground Moving Target Indication in SAR Images using Symmetric Defocusing
              
          
    SAR is not compensating for the doppler of moving targets. It only compensates for the doppler shift of stationary targets
as it assumes that all targets are stationary on Earth.
SAR has side lobes because of which when those capture doppler, they might not suffice Nyquist criterion.
GMTI using Symmetric Defocusing

Abstract

Two filters,which differ only in the signs of the phase responses, are used to defocus the complex image respectively.
In the two defocused images,each stationary target is blurred to the same extent,but each moving target is blurred to different extents.
Therefore, moving targets can be indicated by patch-by-patch sharpness comparison of the two defocused images.

  
## julia-base.ipynb

      
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                Upload this at colab.research.google.com/
              
          
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## skearn-random-forest-example.ipynb

      
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## dataset.csv

          
            card
            reports
            age
            income
            share
            expenditure
            owner
            selfemp
            dependents
            months
            majorcards
            active

            
              yes
              0
              37.66667
              4.52
              0.03326991
              124.9833
              yes
              no
              3
              54
              1
              12

            
              yes
              0
              33.25
              2.42
              0.0052169420000000005
              9.854167
              no
              no
              3
              34
              1
              13

            
              yes
              0
              33.66667
              4.5
              0.0041555559999999995
              15.0
              yes
              no
              4
              58
              1
              5

            
              yes
              0
              30.5
              2.54
              0.06521378
              137.8692
              no
              no
              0
              25
              1
              7

            
              yes
              0
              32.16667
              9.7867
              0.06705059
              546.5033
              yes
              no
              2
              64
              1
              5

            
              yes
              0
              23.25
              2.5
              0.0444384
              91.99667
              no
              no
              0
              54
              1
              1

            
              yes
              0
              27.91667
              3.96
              0.01257576
              40.83333
              no
              no
              2
              7
              1
              5

            
              yes
              0
              29.16667
              2.37
              0.07643376
              150.79
              yes
              no
              0
              77
              1
              3

            
              yes
              0
              37.0
              3.8
              0.2456279
              777.8217
              yes
              no
              0
              97
              1
              6

## __init__.py
from .lsun import LSUN, LSUNClass
from .folder import ImageFolder, DatasetFolder
from .coco import CocoCaptions, CocoDetection
from .cifar import CIFAR10, CIFAR100
from .stl10 import STL10
from .mnist import MNIST, EMNIST, FashionMNIST, KMNIST, QMNIST
from .svhn import SVHN
from .phototour import PhotoTour
from .fakedata import FakeData
from .semeion import SEMEION

## application.csv

          
            reports
            income
            active
            expenditure

            
              0
              4.52
              12
              124.9833

            
              0
              2.42
              13
              9.854167

            
              0
              4.5
              5
              15

            
              0
              2.54
              7
              137.8692

            
              0
              9.7867
              5
              546.5033

            
              0
              2.5
              1
              91.99667

            
              0
              3.96
              5
              40.83333

            
              0
              2.37
              3
              150.79

            
              0
              3.8
              6
              777.8217
card	reports	age	income	share	expenditure	owner	selfemp	dependents	months	majorcards	active
yes	0	37.66667	4.52	0.03326991	124.9833	yes	no	3	54	1	12
yes	0	33.25	2.42	0.0052169420000000005	9.854167	no	no	3	34	1	13
yes	0	33.66667	4.5	0.0041555559999999995	15.0	yes	no	4	58	1	5
yes	0	30.5	2.54	0.06521378	137.8692	no	no	0	25	1	7
yes	0	32.16667	9.7867	0.06705059	546.5033	yes	no	2	64	1	5
yes	0	23.25	2.5	0.0444384	91.99667	no	no	0	54	1	1
yes	0	27.91667	3.96	0.01257576	40.83333	no	no	2	7	1	5
yes	0	29.16667	2.37	0.07643376	150.79	yes	no	0	77	1	3
yes	0	37.0	3.8	0.2456279	777.8217	yes	no	0	97	1	6
	from .lsun import LSUN, LSUNClass
	from .folder import ImageFolder, DatasetFolder
	from .coco import CocoCaptions, CocoDetection
	from .cifar import CIFAR10, CIFAR100
	from .stl10 import STL10
	from .mnist import MNIST, EMNIST, FashionMNIST, KMNIST, QMNIST
	from .svhn import SVHN
	from .phototour import PhotoTour
	from .fakedata import FakeData
	from .semeion import SEMEION