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Hi, I wanted to train a network in GAN fashion in RETURNN i.e. there will be two optimizers discriminator_opt and generator_opt and run them over alternating steps. However, after digging through the …
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Thanks a lot for this project! I'm currently thinking about using Snorkel for a sentiment analysis project I'm working on to label documents and have some basic question as below.
The question that…
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Hi I'm trying the tutorial notebook for categorical classification and got stuck training the generative classifier.
```
from snorkel.learning import GenerativeModel
gen_model = GenerativeMode…
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```
{
"id": "srgan_tensorflow",
"name": "Super-Resolution Generative Adversarial Network (SRGAN)",
"description": "SRGAN trained on the OpenImagesV4 dataset.",
"type": "Image-To-Image Tra…
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https://github.com/pannous/tensorflow-ocr
[Developing a Standard OCR Pipeline The utilization of Pc Imaginative and prescient and Deep Discovering out](http://a1a.in/developing-a-standard-ocr-pipel…
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In both the tutorial examples, after the generative model, neural networks are used as noise-aware discriminative models. Is it possible to use a linear classifier (e.g., logistic regression) as a dis…
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Hi guys,
I'm in a project where I need active spoofing detection using depth information on librealsense sr300. Any idea about how to achieve this? Are there any simple demos? Unfortunately I can'…
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您好,我是搞遥感图像处理的一名研究生,最近看了咱们的论文:A semi-supervised generative framework with deep learning features for high-resolution remote sensing image scene classification,正好找到了对应的代码,但是作为一个菜鸟,好不容易把caffe环境搭建起来了(cpu下…
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Had hard time to understand the output of discriminative model. The discriminative model is the supervised learning. The input is the probability of label y1. What is output x1_1 and x1_2? Are h1_1, h…
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If the generative model produces probabilistic labels, I don't understand why we would feed those into a discriminative model ... the whole purpose was to give a prediction given an input and we have …