Land use land cover image classification using deep learning | EuroSat | ResNet50 | GeoDev

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0:00 Introduction presentation about Image Classification
6:21 About data (EuroSat data)
10:53 Project setup
16:17 Data Preparation
21:29 ResNet50 Model
32:46 Analyzing the Model
38:15 Conclusion

#resnet #deeplearning #LULC

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Thak you so much for your tutorial, I think this type of tutorial is very much helpful for any user if you show the data preparation process using raw data and classify this according to any deep learning process.
Thank you again.

mdabuzafor
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Thank you very much for your tutorial, it will really help all users who wish to use Deep Learning technology to solve their respective problem. However, if you can also show the production process of this model, it will be even more interesting. Because many developers stop after saving and analyzing training results. But do not really affect the deployment of these models under a platform or locally.
In short, if you can also show how to classify land cover features with this model as you often do on Earth Engine with other classification algorithms.
Thank you very much.

filsmagao
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Thank for the tutorial, it is very informative and the quality is outstanding. As @Fils Magao mentionned the deployment part will help me alot

younkapninaduplex
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Thank you for the video, It is really helpful. I need some clarification regarding the dataset used.
In the data description it is said that "A novel dataset based on sentinel-2 satellite images covering 13 spectral bands". However, when I saw the dataset each image has only one layer in .jpg format. All the training and testing were done on these single layered satellite images.
My questions are what is the purpose of all the remaining bands that were used in the dataset generation.?
Does the deep learning models(RESNET50) consider spectral values of the sentinel bands for classification or will it use the color and feature patters from the image.
Thank you in advance.

Geospatiallab
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Hi. It was very helpful for me. Thank you so much.

masoumehbahri
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I have carefully seen your class, thank you very much. I have a question, I understood that you did the classification only for some unknown area based on the Eurosat dataset. That is, training classes and test classes were formed from the Eurosat dataset. Please tell me how can I make a classification for a selected area (say for my city) based on Sentinel 2 using training classes and test classes that I will generate from the Eurosat dataset?

-scgy
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excellent explanation.
please can you provide code to print a batch of predicted images, or maybe a custom image
Please
Thank you

creetikhoo
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Hlo. I m having error while loading the model after epochs. It says no training configuration found in the save file, so the model was not compiled . Compile it manually.. what do i do

Hishma-hk
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Hey. Thank you for the informative video. I have a simple doubt. I am working for crop classification for SAR imagery using CNN and my ground truth dataset is in the shp file format. I want to prepare training and testing files but I am confused for how to separate the SAR imagery based on my ground truth for the training and test files. Can someone help me solve this?
Thanks

tirthapanchal
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Hii sir i need some guidance regarding generating synthetic images with triplegan on Eurosat, can you please help me.... Thanks in advance sir

drakulahits
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thankyou for the video.
are you Nepali by any chance?

arpankhanal
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could you assist me how to create custom dataset like that 10 classes? It will help me a lot.

AkramChowdhury-doxs
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hello and thank you for informative tutorial, I need to visualize my predicted model as a classified map please help me to add this line of code it

hossein.ghafouri.shoreh
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what about the prediction? how can i do it?

theforester_
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Without running epoch we can't get the predicted output

sunilkumardm