medicalAI VS tf2-published-models

Compare medicalAI vs tf2-published-models and see what are their differences.

medicalAI

Medical-AI is a AI framework specifically for Medical Applications https://aibharata.github.io/medicalAI/ (by aibharata)

tf2-published-models

Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard. (by sarus-tech)
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medicalAI tf2-published-models
1 1
15 38
- -
2.7 0.0
11 months ago over 2 years ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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medicalAI

Posts with mentions or reviews of medicalAI. We have used some of these posts to build our list of alternatives and similar projects.
  • Tf 2.0 data API help
    1 project | /r/tensorflow | 20 Jan 2021
    For Vision applications you can use look into this library, https://github.com/aibharata/medicalAI/tree/dev-rc. This branch has tf_image_pipelines in data loaders section. That may be of help to you.

tf2-published-models

Posts with mentions or reviews of tf2-published-models. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-17.

What are some alternatives?

When comparing medicalAI and tf2-published-models you can also consider the following projects:

super-resolution - Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution

differential-privacy - Google's differential privacy libraries.

GLOM-TensorFlow - An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data

dp-xgboost

privacy - Library for training machine learning models with privacy for training data