super-resolution
medicalAI
super-resolution | medicalAI | |
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2 | 1 | |
1,452 | 15 | |
- | - | |
0.0 | 2.7 | |
almost 2 years ago | 11 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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super-resolution
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Is it not possible to get good results in Deep Learning if dataset is small (1000 images)? [D]
https://github.com/krasserm/super-resolution (Super useful for me)
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How to train "models" for opensv edsr (iam super noob)
And thanks ! so it means that I need to train it with one of these trainers inside this project for example https://github.com/krasserm/super-resolution And that means that iam forced to use python (at least for training) but it's OK 🙃
medicalAI
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Tf 2.0 data API help
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.
What are some alternatives?
Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
GLOM-TensorFlow - An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
TrainYourOwnYOLO - Train a state-of-the-art yolov3 object detector from scratch!
SRGAN - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2
SinGAN - Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"