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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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http://doi.org/10.1101/085118 (http://biorxiv.org/content/early/2016/11/02/085118)
> Morphological profiling aims to create signatures of genes, chemicals and diseases from microscopy images. Curre…
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Hello! I've been trying to implement a "mixed network" with part preprocessed features part convolutional architecture. I ran into a bug today that seems to have more general effects: the input dimens…
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### What?
- [CS231n: Deep Learning for Computer Vision](http://cs231n.stanford.edu/) assignments self-study
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I want to reproduce your code and want to run it on Visual Genome1.4 dataset. However, I cannot find the corresponding TXT file for train, val, and test when loading the dataset. Can you put these thr…
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if the image 's size are variable,the output image's size are variable too,so how to build this nn
ghost updated
6 years ago
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Hello,
These models are the models ultimately used for Imagenet classification. I am looking for the pre-trained models used to predict hashtags. From the paper:
"In our experiments, we pre-trai…
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Hello, I have a theoretical problem, in the method part of your paper, that why to multiply A(normalized) with X or L_i? What's the meaning of this multiplication?
ghost updated
5 years ago
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Hi, since training data matters a lot when comparing different methods, could you clarify which datasets the Fast R-CNN detectors in the two provided example models (RGB and DepthJet) have been pre-tr…
tlind updated
5 years ago
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几个目标:
- better
- model
- balancing
- faster