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> We can do segmentation using an existing Convolutional Neural Network by applying it in a Fully Convolutional manner.
> -- [Daniil's blog](http://warmspringwinds.github.io/tensorflow/tf-slim/2016/1…
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related paper
|摘要|
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|We propose a novel semantic segmentation algorithm by learning a deep deconvolution network. We learn the network on top of the convolutional layers adopted from VGG 16-…
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Add the following paper:
* [Fully Convolutional Networks for Semantic Segmentation](https://arxiv.org/pdf/1411.4038.pdf)
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Hello,
I am new to deep neural network. I have started using matconvnet. I am using vgg-f pre-trained network for extracting features. This architecture has 5 convolutional layer and followed by 3 fu…
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Hello! Thanks so much for easyfsl, it's fantastic. I am testing my Prototypical Network (trained on mini imagenet) with SupportSetFolder. When I test it on the folder I attached called dataset1 (conta…
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Thanks for your promising work and your opening-source code.
We are going to follow your work, bur get confusion about your describe about network architecture on svhn dataset.
```
For this exp…
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**Title` of the quantum algorithm**
Demonstration for Quantum Convolutional Neural Network with Chest X-ray Pneumonia Dataset
**Description of the quantum algorithm**
Quantum Convolutional Neur…
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Hi @mikhailocampo
I'm trying to locally debug and reproduce the Kai application, but I've encountered an issue with the Quizzify feature. While everything runs successfully in Docker, I receive th…
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I see `backend_type` parameter in some layer classes constructors such as `convolutional_layer`, `deconvolutional_layer`, `fully_connected_layer`, `max_pooling_layer`, `quantized_convolutional_layer`,…
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Is there a way to visualize/print the outputs of each of the hidden layers in my CNN network? For example my network has two convolutional layers, two max_pooling layers and two fully connected layers…