Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [inception]

46 questions
23
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4 answers

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 3x3 convolutions and applied pooling: What is the…
Martin Thoma
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2 answers

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,…
James
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5
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3 answers

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 me doubt whether there is a bug in my code. I…
tkarahan
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5
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1 answer

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 find any information about it. Just found some…
Vladislav Ladenkov
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4
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1 answer

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 to get through the transfer-learning part, the code…
MetaInformation
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4
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1 answer

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 processing in one-shot learning and have tried the…
thanatoz
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4
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2 answers

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 shar- ing the weights between adjacent tiles. To…
Li haonan
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4
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1 answer

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 that it took anywhere between 2-5 seconds to…
eshirima
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3
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1 answer

difference in between CNN and Inception v3

What is the difference in between the inception v3 and Convolutional neural network?
Muhammad Usman
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3
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0 answers

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 gradient computation phase of back-propagation,…
Gaurav Srivastava
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3
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1 answer

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 Inceptionv3. But for MobileNet models, it does…
James
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2
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0 answers

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 network is 14X14x2048. I used global average pooling…
Krishna Sharma
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0 answers

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 windows. Pulling the tensorflow docker image. docker…
Kantesh Biswas
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2
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1 answer

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 doing wrong. I am following this tutorial
Ravikrn
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2
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1 answer

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. Increasing the activations per tile in a convolutional…
Hossein
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