Questions tagged [convnet]

For questions regarding "Convolutional Neural Networks" (CNN)

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How do I implement the following type of convolution (see picture)? [on hold]

I want to use the following type of convolution in my neural network. Is this a 1-D convolution? How do I implent it in keras / tensorlfow?
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15 views

Keras model with second to last sigmoid activated Conv1D layer followed by globalMaxPool outputs values outside [0,1]. Why?

I am trying to train a binary classifier. It is a residual network with skip layers etc. but ultimately, the bottom two layers are a 1D convolution with sigmoid activation followed by a global max ...
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7 views

MASK RCNN with multicalss classification

I want to create a model which solve a multiclass classification problem. The main concept is: every picture contain only one object the background is very simple all object is coming from the same ...
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1answer
25 views

Model Validation accuracy stuck at 0.65671 Keras

I am using conv1d to classify EEG signals, but my val_accuracy stuck at 0.65671. No matter what changes i do, it never go beyond 0.65671. Here is the architecture ...
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13 views

What transforms do we need to apply to masks of images in segmentation tasks

I am trying a semantic segmentation task for multi-class segmentation. I am wondering what transforms are applied to both images and masks in it. Following are my transforms- ...
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20 views

When do I use Multiply and Add

I want to know the effect of Add and Multiply in keras by functionality. The dumb way of thinking is that they are meant to add ...
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2answers
39 views

Finding Feature Importance in CNN's?

Let's say I have images of cars. For each image in the dataset, I have let's say 3 pictures of the same car but in different angles. 1) The first image is the picture of the car from the front. 2) ...
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23 views

Tensorboard with pytorch dont display a graph

I am trying to visualize a model I created using Tensorboard with Pytorch but when running tensorboard and going to the graph tab nothing is shown, im adding my code for reference, also im adding a ...
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1answer
55 views

Transfer learning on new image size

Transfer learning: Take a trained neural network and use it for a new classification task. When we want to use transfer learning with a convolutional neural network, we don't have to use the same ...
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14 views

How to backpropogate error from convolutional layer with respect to the input when using multiple channels

I have been attempting to implement a Convolutional Neural Network in python and have run into a bit of a roadblock. When backpropogating the error in a convolutional layer let us say that we receive ...
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75 views

Why is training and validation loss steadily rising (eventually to NaN) in this CNN of mine?

Dear ML and data scientists: I have 4 layers of gray scale images for every single biological specimen in my dataset. I am trying to train a 4-convolution CNN (see pytorch architecture below) to ...
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2answers
19 views

ConvNet with concatenated data

I have a basic question regarding convolutional neural network. Assume I have a set of 1000 RGB images and I train a CNN from this set. I can obviously split each of my RGB images into 3 different ...
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1answer
25 views

CNN for unsupervised anomaly detection

I'm wondering if the following strategy has been already used and could work Let's says you have a CNN which work well to classify image data, dog and cat. You only have cat and dog image as training ...
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14 views

How to train a model on image + text features?

So I have a dataset of 6 different dermatology disease pictures along with data of the age, gender, etc other data for each picture. I want to train a model that combines the image and the ...
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41 views

How to use PCA in CNN for image recognition using Keras?

I created a CNN model for image classification and I want to use Principal Component Analysis (PCA) but when I run pca.fit() code, the code still running for hours ...
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13 views

Computing derivatives for backpropagation across a convolution step

This will be a long post, but I hope it'll be instructive to anyone else in my position. I'm trying to find how the derivatives of the loss function are calculated with respect to the kernels and ...
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2answers
22 views

What is the benefit of using Max pooling in convnets as opposed to just using convolution layers? (from Francois Chollet's Deep Learning with Python)

I am reading Francois Chollet's Deep learning with python, and I came across a section about max pooling that's really giving me trouble. I am unable to copy paste the content, so I've included ...
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1answer
46 views

How to merge two CNN deep learning model using weighted sum and weighted product in Keras?

I am using Keras to create a deep learning model and I want to merge two CNNs by using weighted sum or weighted product. How can I merge two CNNs using weighted sum and weighted product?
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14 views

Does a max-pooling layer in a ConvNet contribute to the “vanishing gradient” problem?

I would answer no, but am not sure if I'm missing something and hope you can help me out: The derivative of a max-pooling layer in a ConvNet is one w.r.t. the maximum value and zero for all others. A ...
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1answer
80 views

What is the difference between multiply and dot functions that is used to merge layer in Keras?

I want to merge two CNN deep learning model using Keras and would like to know what is the difference multiply and dot functions that is used to merge layer? ...
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94 views

Input 0 is incompatible with layer conv1d_40: expected ndim=3, found ndim=2

i am working on computer vision using deep learning. my training data contains (x,128) shape. i am passing the same to conv1d layer but facing issues below is my model ...
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1answer
47 views

Triplet loss function for face recognition?

In the Andrew-NG coursera course on Convnets he talked about triplet loss function for one shot face recognition. The formula given in the video is, $$\to \small \small \small ||f(A)-f(P)||^2 \;+\;\...
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1answer
23 views

How many parameters in a Conv2d Layer?

I was following andrew-ng coursera course on deep learning and there's a question that has been asked there which I couldn't figure out the answer for? Suppose your input is a 300 by 300 color (RGB) ...
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28 views

How to design my own keras layer?

I am implementing the paper Perceptual GAN for small object detection. The design is described by the picture given below. I need to design my own keras layer. I have described my code below: The ...
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11 views

why averaging the predictions of 4 models , returns a bad result?

I am working on a multi class classification with eight (8) classes. I tried something at the beginning I thought it was a great idea, but it return utter trash. the experiment: I trained each two ...
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1answer
25 views

Making sense of indices in 2D convolution operations in convolutional neural networks

Referring to the answer here: https://www.quora.com/Why-are-convolutional-nets-called-so-when-they-are-actually-doing-correlations, the equation for a discrete 2D convolution is specified as: $$C(x,y)...
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44 views

Keras Conv1D model Input_shape value error

I am not sure why I am receiving this value error. Additionally, I haven't found a tutorial that explicitly talks about the appropriateness of size of filters and kernel. I would appreciate some input ...
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1answer
30 views

conv net data retrieval on unseen class

I have build a conv net for image classification which work "well" Now I extract features from last fully connected layer and use it for image retrieval (find image most similar to my target image) ...
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1answer
24 views

Reason for Training and test loss sudden increment after some epochs keras

We know that if training and test loss are different from each other, our model is over-fitting. However, if both get high after some epochs, how can we justify it? One way to solve it is to reduce ...
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1answer
51 views

Strange binary classification result with a model that indicate it has been well-trained

The problem : I am trying to build a model for binary classification for melanoma 'MEL' and nevus 'NV' the dataset is from ISIC archive ISIC 2019 but for 8 different type of skin lesion, I am using ...
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3answers
68 views

How can I know if my conv1D model is overfitted or underfitted from loss curve?

I am working on classification of time series multivariate data. By doing PCA, I converted multivariate to uni-variate and fed it into a conv1d in keras. However, I am getting a very high accuracy ...
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23 views

What is the initial size of anchor in Faster R-CNN?

So we generate anchors for input images which will be later used for classification and then regression for bounding box. If we have image size of 224*224*3 and our feature map is of size 7*7*512. ...
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17 views

Object Detection using Faster R-CNN conundrum

So we have our image right? We use some pre-trained model like VGG or Inception which will predict the feature_map. Suppose to a shape of (7,7,512) from the original of (224,224,3). We use this ...
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38 views

TensorFlow: how to restore pre-trained meta model and pass it's weights and biases to the optimizer?

I trained a model on a specific dataset and saved it as a meta, I want to restore the model and use its weights and biases on another dataset the code isn't mine but I'm trying to restore the ...
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6 views

Coreml model inference speed

Comparing the inference speed of my style transfer model on iPhone X vs iPhone 7 vs iPhone XS. Strangely, but the number of frames per second that the model is capable of stylising is pretty much the ...
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Help understanding if suffering from Validation Bias

The goal is to forecast the volume a product will sell in future months. There are about 107 products that are being bought by different customers for different uses. It is univariate problem since ...
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44 views

NCHW vs NHWC in Machine Learning

As I've been introducing myself to the various deep learning frameworks, I've noticed a difference in the default placement of channels for images. Is there a substantial difference between NCHW vs ...
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1answer
52 views

Overfitting CNN models

I tried to develop a number of CNN architectures to train on a 1000-point subset of the "cat-dog" Kaggle training set (meaning, by the way, that all 1000 data points were labeled). I used a 700-150-...
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39 views

Image anomaly detection

I am using a conv net to classify 20 different patterns on an image. My train/test set are images where I know the class. With this, I a good enough model for my preference. It's an unbalance dataset, ...
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2answers
28 views

Unstable results when I train a CNN

I'm currently training a CNN to do a binary classification. I'm getting fairly good results, but unfortunately the training is very unstable. Just by changing the seed the relative error changes by 20-...
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9 views

Open-Set Classification

How can we extend the training process of a classification model to be aware of an open-set task? More plainly speaking, is there a way to train a model on a training set that contains samples from x ...
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6 views

In a CNN do filters that account for depth do so for just the initial input, or for a layers with any depth?

For example, if you have an input of an image of size 100x100x3 (where 3 is the RGB of the image), then put it through a conv layer that results in an output of <...
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25 views

Calculating the Number of Parameters of a 2D CNN Layer

How can I calculate the number of parameters for a 2D CNN layer? I usually use the equation: output width= ((W-F+2*P )/S)+1 = (x) The same answer will be valid for the output height considering that ...
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1answer
28 views

How to perform polynomial landmark detection with deep learning

I am trying to build a system to segment vehicles using a deep convolutional neural network. I am familiar with predicting a set amount of points (i.e. ending a neural architecture with a Dense layer ...
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57 views

Label embedding in Auxiliary Classifier GANs

In Auxiliary Classifier GAN the generator takes two inputs, 1. one hot encoding of the labels, and 2. noise vector. But in the implementation of the GAN (e.g.:) some embedding is used, I think it is ...
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146 views

What is the best architecture for Auto-Encoder for image reconstruction?

I am trying to use Convultional Auto-Encoder for its latent space (embedding layer), specifically, I want to use the embedding for K-nearest neighbor search in the latent space (similar idea to ...
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1answer
84 views

Accuracy improving but, val_acc oscillating in ConvNet. What does it mean?

In my ConvNet model, i'm trying to classify some images. It is malware images and it doesn't contain complex features (i think), as expected model learn to classify images easily. You can see my ...
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1answer
612 views

What is fractionally-strided convolution layer?

In paper Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs, in Section 3.4, it said Since, the aim of this work is to estimate high-resolution and high-quality density maps,...
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187 views

Character segmentation using deep learning

I'm developing a character segmentation algorithm for license plate OCR. My algorithm includes two steps: segmentation and recognition. There is almost no problem for recognition thanks to CNN. My ...
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1answer
70 views

Why can't I use data augmentation with a pretrained convnet?

Reading Deep Learning with Python by François Chollet. In section 5.3.1, we've instantiated a pretrained convnet, VGG16, and are given two options to proceed: A) Running the convolutional base over ...