We’re rewarding the question askers & reputations are being recalculated! Read more.

Questions tagged [convolutional-neural-networks]

For questions about convolutional neural networks, also known as CNN or ConvNet.

Filter by
Sorted by
Tagged with
4
votes
3answers
4k views

Traffic signs dataset

I'm looking for annotated dataset of traffic signs. I was able to find Belgium, German and many more traffic signs datasets. The only problem is these datasets contain only cropped images, like this: ...
2
votes
4answers
163 views

Using Convolutional Neural Networks for movement classification

I have programmed my first network for the MNIST dataset. I was wondering what the first approach would be to recognize certain movements. I have read about that the time dimension should be ...
-1
votes
1answer
154 views

Using 3D Points as Inputs to a Neural Net

I am currently looking to use a neural network to classify gestures. I have a series of Dx,Dy,Dz readings that represent the differences across the three axes made during the gesture. About 10 ...
2
votes
0answers
34 views

Autoencoder why it is special for image decoding?

I have read about auto encoder. Understood what is encoding part, and decoding part, and the latent space. Now, i tried to implement this in keras. Below is the code. ...
3
votes
1answer
91 views

Can a basic CNN (Conv2D, MaxPooling2D, UpSampling2D) find a good approximation of a product of its input channels?

Let's assume I want to teach a CNN some physics. Starting with a U-Net, I input images A and B as separate channels. I know that ...
1
vote
1answer
42 views

Fundamentally choosing number & size of filters, convolution layers in deep learning

While we train a CNN model we often experiment with number of filters, number of convolutional layers, FC layers, filter size, sometimes stride, activation function, etc. More often than not after ...
1
vote
0answers
9 views

How do we stack two U-Nets to yield one final prediction?

I am trying to reproduce this paper's model, i.e. stacking two U-Nets to yield one final prediction. The paper mentions that: The deconvolution features of the first U-Net and the intermediate ...
1
vote
2answers
55 views

CNN Pooling layers unhelpful when location important?

I'm trying to use a CNN to analyse statistical images. These images are not 'natural' images (cats, dogs, etc) but images generated by visualising a dataset. The idea is that these datasets hopefully ...
1
vote
1answer
97 views

How can I classify relevant and irrelevant images from the Database?

I have a mixed image database(unstructured data). In the database there are some images that i am interested in and I want to discard the rest by using cnn. I am not looking for specific objects in ...
3
votes
1answer
269 views

Convolutional Layers on a hexagonal grid in Keras

Keras' convolutional and deconvolutional layers are designed for square grids. Is there was a way to adapt them for use in hexagonal grids? For example, if we were using axial coordinates, the input ...
2
votes
2answers
74 views

Dimensionality of convolutional layers & convolution operations

I am trying to understand the dimensionality of the outputs of convolution operations. Suppose a convolutional layer with the following characteristics: Input map $\textbf{x} \in R^{H\times W\times D}...
1
vote
0answers
41 views

Doubt regarding research paper on Crowd Counting using Convolutional neural networks and Markov Random Field

I am currently reading the research paper Image Crowd Counting Using Convolutional Neural Network and Markov Random Field by Kang Han, Wanggen Wan, Haiyan Yao, and Li Hou. I did not understand the ...
3
votes
2answers
150 views

Can I reduce the “number of weights” in CNN to 1/3 by restricting the input as greyscale image?

In a CNN, does each new filter have different weights for each input channel, or are the same weights of each filter used across input channels? This question helps me a lot. Let, I have RGB input ...
2
votes
1answer
69 views

Clarification regarding “Image Crowd Counting Using Convolutional Neural Network and Markov Random Field”

I am currently reading the research paper Image Crowd Counting Using Convolutional Neural Network and Markov Random Field by Kang Han, Wanggen Wan, Haiyan Yao, and Li Hou. I did not understand the ...
1
vote
1answer
132 views

Occupation detection using Face API

For my university project, I am planning to build a face recognition/ occupation recognition programme. However, rather than using the existing Haar cascade(for age and gender) I am planning to use ...
2
votes
2answers
451 views

How to architect a network to find bounding boxes in simple images

I have an application where I want to find the locations of objects on a simple, relatively constant background (fixed camera angle, etc). For investigative purposes I've created a test dataset which ...
10
votes
2answers
2k views

Which layer consumes more time in CNN training ? Convolution layers vs FC layers

In Convolutional Neural Network, which layer consumes maximum time in training? Convolution layers or Fully Connected layers? We can take AlexNet architecture to understand this. I want to see time ...
1
vote
1answer
2k views

Counting people in an image of a crowd

What are some good approaches that I can use to count the no. of people in a crowd. Tracking each person individually is obviously not an option. Any good approaches or some references to research ...
8
votes
2answers
500 views

What benefits can be got by applying Graph Convolutional Neural Network instead of ordinary CNN?

What benefits can we got by applying Graph Convolutional Neural Network instead of ordinary CNN? I mean if we can solve a problem by CNN, what is the reason should we convert to Graph Convolutional ...
-1
votes
1answer
266 views

Simple Object Detection

I want to create a simple Object detection tool. So basically an Image will be provided to the tool and from that, it has to detect the number of objects. For eg An image of a dining table which ...
4
votes
1answer
57 views

Optimizing image recognition results for unknown labels

I’m training a network to do image classification on zoo animals. I’m a software engineer and not an ML expert, so I’ve been retraining Google’s Inception model and the latest models is trained ...
3
votes
1answer
42 views

Figuring out mapping between two matrices

Imagine I have a 2D matrix, A. I apply some transformation to it, for example: B = A_shifted + A. Would it be possible to train a CNN to learn back the mapping from B to A? Giving B as example and A ...
3
votes
1answer
109 views

How to tinker with CNN architectures?

I was thinking of creating a CNN. Now it is known CNN takes long times to train so it is advisable to stick to known architectures and hyper-parameters. My question is: I want to tinker with the CNN ...
1
vote
0answers
51 views

YOLO - How much is the position of the object relevant in learning?

I have the following question about You Only Look Once (YOLO) algorithm, for object recognition in CNNs. I have to develop a neural network to recognize web components in web applications - for ...
4
votes
1answer
44 views

How to compare the training performance of a model on different data input?

So I have a deep learning model and three data sets (images). My theory is that one of these data sets should function better when it comes to training a deep learning model (meaning that the model ...
4
votes
1answer
725 views

Training a CNN from scratch over COCO dataset

I am using Tensorflow Object Detection API for training a CNN from scratch on COCO dataset. I need to use this specific configuration. There is no pre-trained model on COCO with that configuration and ...
4
votes
1answer
2k views

How to train a CNN

When it comes to CNNs, I don't understand 2 things in the training process: How do I pass the error back when there are pooling layers between the convolutional layers? And if I know how it's done, ...
4
votes
1answer
70 views

How should continuous action/gesture recognition be performed differently than isolated action recognition

I am going to train a deep learning model to classify hand gestures in video. Since the person will be taking up nearly the entire width/height of the video and I will be classifying what hand gesture ...
4
votes
2answers
124 views

What is the best approach for writing a program to identify objects in a picture then crop them a specific way?

My works quality control department is responsible for taking pictures of our products at various phases through our QC process and currently the process goes: Take picture of product Crop the ...
4
votes
2answers
183 views

Image Classification

I am currently working on a project to classify snake types separately using an image of the snake. I need to train a module to classify snake images, but the problem is there are only a small number ...
3
votes
1answer
118 views

Double pooling layers

In what scenario when assembling a DL CNN would you want to have two adjacent pooling layers, without a convolutional layer between?
3
votes
1answer
793 views

Optimizing Max Pooling Algorithm

The below code is a max pooling algorithm being used in a CNN. The issue I've been facing is that it is offaly slow given a high number of feature maps. The reason for its slowness is quite obvious-- ...
3
votes
1answer
85 views

Disentangled VAE doesn't reconstruct accurate grids

I am trying to implement the disentangled VAE model according to this link. I want to understand the architecture of this model in order to customize it later. As infrastructure, I have a linux kernel ...
1
vote
0answers
140 views

Backpropagation of convolutional neural network - confusion [closed]

I've already seen many articles about this topic and Backpropagation In Convolutional Neural Networks by Jefkine (5 September 2016) seems to be the best. Although, as author said, For the purposes ...
4
votes
2answers
117 views

Loss function for singular object detection

What loss function should one use, knowing that input image contains exactly one target object? I am currently using MSE to predict center of ROI coordinates and it's width and height. All values ...
7
votes
6answers
1k views

Why Python not C?

I like the enforced indentation of Python that many don't like because I hate parenthetic typing and redundant semicolons. I like the shell interface, but why do some think Python is de facto for ...
4
votes
1answer
323 views

Identifying car model via deep learing

Is there any project or example for a software identifying cars? Situation: I got multiple angle shots in high resolution from a car. I want the algorithm to tell me "This is a Mercedes SLK" or "This ...
1
vote
0answers
26 views

In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters?

I know that the first layer uses a low-level filter to see the edge information. As the layer gets deeper, it will represent high-level (abstract) information. Is it because the combinations of ...
1
vote
0answers
71 views

Using CNN LSTMs for prediction of images from image series

I have the following setup for a prediction task: I want to predict entire pictures from previously given pictures. In my case, only 2 pixels in every frame are neither black nor white, they are some ...
1
vote
0answers
64 views

How do GAN's generator actually work?

I have implemented DCGAN's myself and have been studying GAN's for over a month now. Now I am implementing the pggans but I encountered a sentence When we measure the distance between the ...
1
vote
1answer
553 views

How to label training data for YOLO

I am having a question on how to label training data for YOLO algorithm. Let's say that each label Y, we need to specify [Pc, bx, by, bh, bw], where Pc is the indicator for presence(1=present, 0=not ...
11
votes
3answers
918 views

What topologies are largely unexplored in machine learning?

Geometry and AI Matrices, cubes, layers, stacks, and hierarchies are what we could accurately call topologies. Consider topology in this context the higher level geometrical design of a learning ...
9
votes
4answers
594 views

Beyond neural networks?

Are there possible algorithms that have the potential to replace neural nets in the near future? And do we need that? What is the worst thing of using neural networks in terms of efficiency?
2
votes
1answer
52 views

Are there benchmarks for assessing the speed of the forward-pass of neural networks?

I have a task where I would like to use a convolutional neural network (CNN). I would like to incrementally start from the fastest models, fine-tune and see whether they fit my "budget". At the moment,...
3
votes
5answers
2k views

CNN with OpenCV

I have practiced building cnn for image classification with tensorflow, luckily to me they have very good library documentation and tutorials. But i found that tensorflow is too complicated, building ...
3
votes
1answer
541 views

Regarding Yolo and Keras

I'm trying to implement YOLO (tiny version, v1) into Keras framework. For the past two days, I've been relentlessly digging through Github and the likes in order to ...
2
votes
1answer
131 views

Neural network architecture for line orientation prediction

Imagine that a line divides an image in two regions which (slightly) differ in terms of texture and color. It is not a perfect, artificial line but rather a thin transition zone. I want to build a ...
2
votes
1answer
54 views

What are some resources regarding the complexity of training neural networks?

In the paper "Provable bounds for learning some deep representations", an autoencoder like a model is constructed with discrete weights and several results are proven using some random-graph theory, ...
0
votes
1answer
125 views

Using CNN to identify buildings from aerial images

I want to train a CNN (Vggnet) to identify different types of buildings from aerial images. However seeing that a CNN "ignores" size, e.g. the same type of dog in one image can be large and small in ...
7
votes
3answers
205 views

CNN's vs Densely Connected NN's

In image classification we are generally told the main reason of using CNN's is that densely connected NN's cannot handle so many parameters (10 ^ 6 for a 1000 * 1000 image). My question is, is there ...