Questions tagged [inception]
The inception tag has no usage guidance.
46 questions
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Number of input and output channels of MAX POOL layer
This is what Andrew Ng draws in his pooling layers video in the Coursera Deep Learning Specialization:
and this is what he draws in Inception network video:
Notice in first slide, number of input ...
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Is there wights of voice or audio for VGG or Inception?
I want to use VGG16 (or VGG19) for voice clustering task.
I read some articles which suggest to use ...
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Using vgg16 or inception with wights equals to None
When using pre-trained models like vgg16 or inception,
it seems that one of the benfits of using pre-trained model, is to save ...
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Testing accuracy very low, while training and validation accuracy ~ 85%
I have a training dataset of 10000 pictures and a test dataset of 15000 pictures. There are 23 types of birds.
First of all, I imported the necessary
...
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About multiple objectives in Inception networks
Inception networks, in contrast to most of the networks, can have multiple outputs, from which the gradient can propagate in order to update the weights.
These outputs can have different size and ...
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How does bottleneck layer reduce computations without compromising with performance?
I was reading an article explaining the google's inception model . There it was mentioned , that to reduce the number of computations , we use a bottleneck layer. But I was surprised , if the model ...
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Is it possible to use Inception Model in GANs (DCGAN) using PyTorch(or any other library)?
MAIN ISSUE:
Is it possible to use Inception Model (e.g. v3) for DCGAN using PyTorch(any other library)?
I've tried to find info how it could be implemented but nothing has been found.
It was explained ...
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786
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Using CNN on one class only
I want to use InceptionV3 on one class of image (ie. to detect one type of object/one label only). For example, to detect 'penguin' or 'no penguin'. All my images have been cropped down to mostly ...
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What is an optimal local sparse structure of a convolutional vision network?
I was reading the InceptionNet Paper, where I found quite a few references to developing a sparse network structure, but I am not clear on what this means.
An ...
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Keras Model Predict is not predicting all images flowing from directory?
I have the following code where I have done all the training and passed the testing set as a flow from directory. After that when I pass that object into the model.predict option, the array received ...
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Error when trying Transfer Learning
I'm trying to train a model which is an extension of Google's Inception-V3 for the purpose of recognizing and classifying whether there is any pneumonia using x-ray images.
I've used Tensorflow-Hub ...
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CNNs: understanding feature visualization Channel Objectives (SOLVED)
I'm trying to follow a paper on deep NN feature visualization using beautiful examples from the GoogLeNet/Inception CNN. see: https://distill.pub/2017/feature-visualization/
The authors use ...
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How to compute Frechet Inception Score for MNIST GAN?
I'm starting out with GANs and I am training a DC-GAN on MNIST dataset. The two metrics that are used to evaluate GANs are Inception Score (IS) and Frechet Inception Distance (FID). Since Inception ...
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Confusion regarding prediction results of SVM and ANN on feature vectors
I am making a custom image classifier using Transfer Learning on Inception V3. I have 3 classes of images with ~6K images each. The input dimension of the network is 500X500 and the output of the ...
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Dealing with pre-trained model for grayscale images
I would like to do Transfer Learning using one of the novel networks such as VGG, ResNet, Inception, etc.
The problem is that my images are grayscale (1 channel) since all the above mentioned models ...
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Very Fast Training After First Epoch
I trained an InceptionV3 model using plant images. I used Keras library. When training was started, first epoch took 29s per step and then other steps took approximately 530ms per step. So that made ...
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Retrain image classifier using MobileNet v2
I am using my own dataset to retrain mobilenet_v2_100_224 model, I currently have 4 classes where each class have more than 100 images still I'm observing overfitting even though I've used ...
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Why is the GoogLeNet retrained model size less compared to others?
I have some questions if someone can answer me or guide me articles to understand them. I investigated different pre-trained model i.e. AlexNet, VGG, GoogLeNet, InceptionV3 and ResNet. I have ...
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Image features (produced by VGG19) do not properly train an ANN in Keras
I've used a VGG16 network to extract features from an image dataset, creating a features dataset using the following code:
...
user42078
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Which is the fastest image pretrained model?
I had been working with pre-trained models and was just curious to know the fastest forward propagating model of all the computer vision pre-trained models. I have been trying to achieve faster ...
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how to visualize InceptionV3 hidden layers
I am following google codelab:
Tensorflow for poet to train my custom model. This google codelab use the Inception-V3 model for training.
The inception-V3 model have 48 layer. My question is that ...
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difference in between CNN and Inception v3
What is the difference in between the inception v3 and Convolutional neural network?
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Training Inception V3 based model using Keras with Tensorflow Backend
I am currently training a few custom models that require about 12Gb GPU memory at the most. My setup has about 96Gb of GPU memory and python/Jupyter still manages to hog up all the gpu memory to the ...
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What are towers in inception architecture and tensorflow?
My understanding of towers in inception architecture and in tensorflow terminology is that they are part of a neural network model for which separate computation can happen on forward phase and ...
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Pretrained InceptionV3 - very low accuracy on Tobacco dataset
I'm trying to fine-tune a pre-trained InceptionV3 on the tobacco-3482 document dataset (I'm only using the first 6 classes), but I'm getting accuracies under 20% on the validation set (> 90% accuracy ...
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Where to find list of Tensorflow pretrained models available in download.tensorflow.org/models
I am trying the find the pretrained models (graph.pd and labels.txt) files for Tensorflow (for all of the Inception versions and MobileNet)
After much searching I found some models in, https://...
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Running Tensorflow MobileNet from Java
I am trying to run Tensorflow for image recognition (classification) in Java (JSE not Android).
I am using the code from here, and here.
It works for Inceptionv3 models, and for models retrained from ...
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python.framework.errors_impl.permissiondeniederror
I am trying to retrain inception final layer on new set of images. I am using docker TensorFlow image on Windows environment. Below are the steps that I am following.
Install docker toolbox for ...
2
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1
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789
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Transfer learning (on pre-trained inception net model) for multi label classification is giving similar probability for all labels
Number of labels: 1000, Dataset size: 200000 images
Final probability for 1000 labels is in the range of 0.3 to 0.34.
I was expecting large variation in probabilities. Can someone tell me what I am ...
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Some questions about GoogleNet paper
This phrase is from the "Rethinking the Inception Architecture for Computer Vision" paper. it says :
Higher dimensional representations are easier to process locally within a network. ...
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Transfer learning within Tensorflow's inception model
I want to freeze the layers, except the first three layers, in the Inception v3 model with TensorFlow in Python 3, and modify the weights of these three layers to be able to re-initialize and re-train ...
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How does inception decrease the computational cost?
From the second paragraph of 3.1 Factorization into smaller convolution in the paper Rethinking the inception architecture for computer vision:
This setup clearly reduces the parameter count by ...
- 141
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What is the reason behind the minimum image size in the Keras InceptionResNetV2 model?
In Keras' documentation for the InceptionResNetV2 model, it says the following:
input_shape: (...). It should have exactly 3 inputs channels, and width and height should be no smaller than 139.
I'...
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TensorFlow Inception V3
What are bottleneck values and how are they generated?
How does the next-to-last layer of Inception use these bottlenecks to generate the accuracy?
How is the final accuracy calculated?
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Inception/ResNet doing worse than SIFT in feature extraction
We are doing our Thesis on multimodal retrieval. it's basically searching different modalities (multimedia ex: text, video, images ...) with other modalities. i.e. searching a database of images with ...
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Tensorflow and OpenCV real-time classification
I am testing the machine learning waters and used TS inception model to retrain the network to classify my desired objects.
Initially, my predictions were run on locally stored images and I realized ...
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Transfer learning inceptionv3
Why is training classifier on extracted features (from inceptionV3) is so much faster than simply stack classifier on topless inception model?
From my experience extracting features + training ...
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Understanding Imagenet training
I am trying to start training Imagenet classification training using Tensorflow's inception model. I am a bit confused as I am not sure how to fully train the model.
Wherever I go everyone seems to ...
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Fine-tuning a model from an existing checkpoint with TensorFlow-Slim
I'm trying to retrain the final layer of a pretrained model with a new image dataset using TensorFlow-Slim.
Lets say I want to fine-tuning inception-v3 on flowers dataset. Inception_v3 was trained ...
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Retrain final layer of Inception model
I'm trying to retrain Inception model final layer for a binary classification.
My training image set contain 2000 images in class 1 and more than 6000 images in class 2.
Will this huge difference in ...
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Inception V3 Running Stats?
Has anyone created statistics on how fast and accurate Inception V3 can classify an image based on criteria such as: different models of GPUs/CPUs, input image size, input image ratio, file format, ...
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Using TensorFlow's preexistent Inception labeler
I know I can retrain Inception to label images, but can I just provide an image to a non retrained Inception and get a label back?
- 115
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How to use InceptionV3 without retraining
I know I can retrain Inception to label images, but can I just provide an image to an untrained Inception and get a label back? Is there an API for this? If there is, then why does Google open source ...
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What is the difference between Inception v2 and Inception v3?
The paper Going deeper with convolutions describes GoogleNet which contains the original inception modules:
The change to inception v2 was that they replaced the 5x5 convolutions by two successive ...
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What is an inception layer?
I'am reading an article called "FaceNet: A Unified Embedding for Face Recognition and Clustering". And there, they use something called "inception". I guess it's something about layers, but I can't ...
