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### Team Name:
Penn Ave Fish Company
### Project Description:
#### Introduction
A prerequisite for quantum algorithms to outperform their classical counterparts lies in the ability to ef…
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Imbalanced dataset is relevant primarily in the context of supervised machine lea…
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**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
Yes, Image Super-Resolution (ISR) is directly related to solving specific…
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Overview
In the final lesson of Practical Deep Learning for Coders we'll study one of the most important techniques in modern architectures: the skip connection. This is most famously used in the res…
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Traceback (most recent call last):
File "D:/python file/Super-Resolution-using-Generative-Adversarial-Networks-master/models.py", line 10, in
from keras_ops import fit as bypass_fit, smooth_g…
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On the Effectiveness of Least Squares Generative Adversarial Networks
https://arxiv.org/pdf/1712.06391.pdf
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A deep convolutional generative adversarial network implemented in PyTorch! The project is designed to generate realistic images from random noise using the power of deep learning.
This project illus…
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Dear Yunjey Choi,
I read your CVPR paper, "StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation", in which you refer to using Amazon Mechanical Turk (A…
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These days, 'Domain-Adversarial Training of Neural Networks' (https://arxiv.org/abs/1505.07818) is getting attention in Generative Adversarial Networks and domain adaptation learning.
It's already im…
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**Chapter 17 - Robust AI**
- First and foremost, this chapter was incredibly long -- nearly double the size of some of the other lengthier chapters in this book. It was so much material that it was…