medicalAI VS GLOM-TensorFlow

Compare medicalAI vs GLOM-TensorFlow and see what are their differences.

medicalAI

Medical-AI is a AI framework specifically for Medical Applications https://aibharata.github.io/medicalAI/ (by aibharata)
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medicalAI GLOM-TensorFlow
1 4
15 36
- -
2.7 0.0
11 months ago about 3 years ago
Python Python
Apache License 2.0 Apache License 2.0
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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.

GLOM-TensorFlow

Posts with mentions or reviews of GLOM-TensorFlow. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing medicalAI and GLOM-TensorFlow you can also consider the following projects:

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

InvoiceNet - Deep neural network to extract intelligent information from invoice documents.

image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

efficientnet-lite-keras - Keras reimplementation of EfficientNet Lite.

image-quality-assessment - Convolutional Neural Networks to predict the aesthetic and technical quality of images.

wtte-rnn - WTTE-RNN a framework for churn and time to event prediction

cnn-raccoon - Create interactive dashboards for your Convolutional Neural Networks with a single line of code!

ydata-synthetic - Synthetic data generators for tabular and time-series data

head-pose-estimation - Realtime human head pose estimation with ONNXRuntime and OpenCV.

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.

Speech_driven_gesture_generation_with_autoencoder - This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".

nodding-pigeon - Detection and classification of head gestures in videos