Questions tagged [convnet]

For questions regarding "Convolutional Neural Networks" (CNN)

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23 views

Finding the appropriate CNN Model Architecture and Parameters

I am currently creating a CNN model that classifies whether the font is Arial, Verdana, ...
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30 views

Is it possible to train YOLO (or other object detectors) from the raw architecture, rather than cloning\downloading it?

I am trying to do object detection but I am faced with some issues. I cannot install YOLO, or any other existing models that require cloning a repo, and a certain number of other limitations. ...
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17 views

Precision Recall using Distance Matrix

Given a Pre-trained CNN model, I extract feature vectors for 3450 Reference (Winter) and 3450 Query images (Spring) and compare features with euclidean distance to plot the distance matrix besides ...
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1answer
84 views

EfficientNet: Compound scaling method intuition

I was reading the paper EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks and couldn't get my head around this sentence: Intuitively, the compound scaling method makes sense ...
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84 views

Fusing batch normalization with deconvolution in neural networks

I am trying to raise the performance of my convolutional neural network and for that reason I am trying to implement batch normalization fusing. Things are fine when I use fuse with convolution layer,...
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14 views

What is the current state-of-the-art, out-of-the-box alternative to Darknet YOLO?

I am unfortunately unable to use YOLO. I am trying to implement another solution. Ideally, this would be a neural network architecture with weights that I could import easily like any other Keras/...
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21 views

What does “context” mean in the context of computer vision models

I'm reading this research paper and I do not understand what they mean by "high level context".
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12 views

Can one hardcode convolutional filters to detect characters in a CNN?

In Pytorch, you can hardcode your filters to be whatever you like. At the moment, I'm doing text detection and I need to identify the location of a certain information. This information always ...
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25 views

In what form the optical flow data is fed to a 3d cnn model?

I want to create a 2 stream architecture for video classification using keras and tensorflow as its back-end .In this method you basically give 2 types of data to the model.One is the video itself(...
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21 views

Why does this implementation of SimpleNet use 3x3 kernels on it's final layer for cifar10?

Question; I'm trying to implement simplenet in tensorflow and I have a question that I can't seem to answer myself. The implementation I'm basing this off of is here: https://github.com/Coderx7/...
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1answer
224 views

What do positive and negative gradient values mean for Convolutional Neural Network?

As we have the typicall pass of the neural network we make a forawrd pass to predict classes and then we have cost function and based on that we calculate gradients. I'm wondering what are the ...
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42 views

Understanding the significance of LeNet-5 w/ MNIST data set

I'm beginning to learn about conv nets and started with what I understand to be one of the seminal works: LeNet-5. However, my limited experimentation doesn't seem to show any advantage over a single ...
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1answer
49 views

How neural style transfer work in pytorch?

I am using this pytorch script to learn and understand neural style transfer. I understood most part of the code but having some hard time understanding some parts of the code. In ...
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97 views

Why is convnet transfer learning taking so long?

I am using transfer learning to train a binary image classification model using keras' pretrained VGG16 model. The code can be found below : ...
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1answer
31 views

How do CNNs find different feature maps?

Assume I have a CNN that in the first (conv) layer takes a 1-channel signal (the input) and gives a 2-channel output. Let's further assume that the rest of the net has symmetric architecture from the ...
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17 views

Train a competitive layer on nonnormalized vectors using LVQ technique

How can we train a competitive layer on non-normalized vectors using LVQ technique ? The net input expression for LVQ networks calculates the distance between the input and each weight vector ...
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2answers
33 views

How to extract crucial features to create an image

Imagine, you have a dataset containing pictures of (example only, just to explain the task) cats and dogs. The data set is labeled, so we can train using supervised learning algorithms. My goal is to ...
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1answer
43 views

Which combination of 3 hyperparameters to combat overfitting of a convolutional neural network?

I have a small dataset with which I want to train a CNN by using Data Augmentation. Since the CNN is overfitting due to the small data set, I would like to optimize some hyperparameters. However, ...
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1answer
82 views

Tensorflow Conv3D with variable input size

I have a hypotethical question: Is it possible to train Conv3D with variable input size? Sample dim = Length x Width x Depth ; Depth are fixed per each samples, let's say 500. However Length x Width ...
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10 views

Modifying network to handle images consistently

I'm modifying IRNet to work with the Cityscapes dataset. This network takes images as input and is supposed to output images that can be used as instance segmentation labels. IRNet originally uses ...
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1answer
65 views

Improve performances of a convolutional neural network

I am doing image classificaition, and to do this I have built the following neural network: ...
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1answer
30 views

Validity of PU learning while using character-level encoding using CNNs for classifying text data

I'm trying to classify a large set of documents (~100M) as valid or invalid, based upon a small given set of labeled valid documents (~3k). I'd like to know if the PU learning approach described in ...
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2answers
360 views

Model not learning when using transfer learning

I am working on a personal project on image classification (two classes) and am trying to see how the MobileNet v2 structure would perform. While training the training accuracy is already quite high ...
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0answers
13 views

if two convolution layer connected in tandem follow associative property of convolution?

Two Convolution filter follow the associative property as follows :- I want to ask whether this property will hold for two convolution layer with no operation in between them?
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1answer
34 views

To calculate my confusion matrix with recall and precision, my test set need to be equal(balanced)?

In my CNN, I have 200 'negative' images and 50 'positive' images in my test set and I want to make a confusion matrix. My doubt is if I have to equalize the samples in the dataset because if I keep ...
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116 views

Python Keras model performs much worse than R Keras model

I got this R Keras model from GitHub that performs really well. GitHub repo ...
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1answer
162 views

Why/When should I use VGG16 to do fine-tuning? [closed]

Why or When should I use VGG16 in my cnn? what is the pros and cons to use this model? I search but not found this answer. If you have references, I appreciate
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3answers
2k views

How to combine GridSearchCV with Early Stopping?

I'm a beginner in machine learning and want to train a CNN (for image recognition) with optimized hyperparameter like dropout rate, learning rate and number of epochs. The optimal hyperparameter I ...
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0answers
36 views

Why when I apply GaussianBlur in my images, my model overfit? CNN KERAS

I have 1400 images (700 each class), and i'm using vgg-16 to classificate between one and other class. But when I apply the preprocess method Gaussian Blur (which seem to be very much clear to see the ...
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65 views

Combining 2D Detection with Disparity Maps to Learn 3D Object Geometry

Since the disparity map above is a representation of the object's distance from the camera's origin, is it reasonable to assume that a network (perhaps a convolutional LSTM) could be trained to ...
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0answers
35 views

Did I do the right thing in my CNN Keras (class imbalance - augmentation)

To implement my Binary CNN in keras, I had a dataset of ~~35000 images but only 700 is from one class and all the others are from the other class, so what I did: I get the 700 unique images from class ...
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39 views

How do I augment data after spliting traininng datset into train and validation set for CIFAR10 using PyTorch?

When classifying the CIFAR10 in PyTorch, there are normally 50,000 training samples and 10,000 testing samples. However, if I need to create a validation set, I can do it by splitting the training set ...
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1answer
69 views

What is a latent space vector?

I do not understand this about GANs. Apparently the Generator is supposed to receive a latent space vector as its input. Yet I couldn't find an example of how I can implement it in Pytorch. This is a ...
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24 views

CNN model with transfer learning not performing, training loss is still high, test accuracy is very low

Hi I'm trying to train a cnn model with transfer learning, and I am not able to get a good test accuracy (14%) - I don't know why it doesn't work for me. ...
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2answers
149 views

Why are my predictions bad, if my accuracy in train is roughly 100% (Keras CNN)

In my CNN i have to handle 2 classes in a binary system, I have 700 images each class to train, and others to validation. This is my train.py: ...
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0answers
18 views

What is the difference between these 2 training scenarios?

I have a very large dataset and due to computational constraints, I have to divide the data into 20 parts (each part is around 1.5GB). I constructed a deep CNN model using Keras for this dataset. The ...
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0answers
18 views

Process with which ImageDataGenerator with flow_from_directory() method fetches and augments images from a directory in Keras 2

When using Keras 2.0 ImageDataGenerator and in particular the flow_from_directory() method to perform data augmentation, how many images are generated and in what order? Do we have a way to control ...
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0answers
65 views

Shuffling the images with DataImageGenerator and flow_from_directory in a Medical application (tensorflow 2/Keras)

I am facing the following situation: I have CT images (scans) of patients where 10 images describe each patient. These images are stored in separate directories based on what is the focus of each ...
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0answers
92 views

ResNet50 Model is not learning with transfer learning in keras

I am trying to perform transfer learning on ResNet50 model pretrained on Imagenet weights for PASCAL VOC 2012 dataset. As it is a multi label dataset, I am using ...
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2answers
42 views

What does Conv1d do in a sentiment analysis?

I am doing some study on https://www.kaggle.com/anshulrai/cudnnlstm-implementation-93-7-accuracy I understand we need LSTM to capture the sequence of words in the sentience, but I am not quite ...
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1answer
277 views

MobileNet and MobileNetV2: Bad Inference Results

unfortunately I am having subjectively bad results in inference with pre-trained models of both MobileNet v1 and v2: ...
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0answers
18 views

What is the use of having shared weights in later layers of a CNN?

In a CNN, all the neurons in a single layer use the same weights and bias. As a result, all the neurons detect the same feature. The early layers of a CNN detect simple features like edges and hence ...
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1answer
122 views

Are CNNs indeed translation invariant?

I read that in a hidden layer of a convolutional neural network, all neurons share the same weights and bias. As a result, all the neurons detect the same feature and hence ConvNets become invariant ...
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1answer
317 views

How to increase the accuracy of my predictions (CNN fine tuning VGG16 KERAS)

In my VGG16 fine-tuning, I have to classify retinal images in 2 classes (or 4th stage or not 4th stage) and I have 700 images each class to train. This is my code now: ...
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3answers
78 views

Problem with overfitting

I make small CNN from scratch to classify barcodes. I have two classes: one for images with barcodes and second for all what isn't barcodes (items, animals, landscape, furniture, people). I got good ...
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2answers
21 views

Choosing a set of CNNs for paper

There are so many CNNs out there and im trying to do a comparison between some of them in my paper which networks should I use? Resnet, vgg and inception are obvious but I need 3 or 4 others. which ...
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0answers
32 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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3answers
2k 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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1answer
39 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
472 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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