Xvision | Chest Xray image analysis using Deep learning | Machine Learning library
kandi X-RAY | Xvision Summary
kandi X-RAY | Xvision Summary
Chest Xray image analysis using Deep Learning and exploiting Deep Transfer Learning technique for it with Tensorflow. The maxpool-5 layer of a pretrained VGGNet-16(Deep Convolutional Neural Network) model has been used as the feature extractor here and then further trained on a 2-layer Deep neural network with SGD optimizer and Batch Normalization for classification of Normal vs Nodular Chest Xray Images.
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Top functions reviewed by kandi - BETA
- extract a single image from url
- Return a VGG16 model .
- Preprocess the image
- Extract links from URLs .
- Get the content feature of the image .
- Deprocessing an image .
Xvision Key Features
Xvision Examples and Code Snippets
Community Discussions
Trending Discussions on Xvision
QUESTION
In my T-SQL I have following query:
...ANSWER
Answered 2022-Feb-01 at 09:03You can try to use the aggregate function to get the value, then use STUFF
function with self-join to make like string_agg.
you can use
string_agg
function if your sql-server version supported it.
QUESTION
Target and source files are both xml type files.
I have a hard time using sed
because it does not work well with special characters and those xmls are full of them.
I researched that there's a way of doing it with awk
and here's my problem because I have a really hard time using awk
Edit:
Main xml file with marked position:
...ANSWER
Answered 2021-Aug-24 at 13:22In case no-one can come up with a solution for you using an XML-aware tool, this might be all you need:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Xvision
You can use Xvision like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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