Questions tagged [convolutional-neural-networks]

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

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44 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 ...
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2answers
181 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 ...
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1answer
76 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
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1answer
149 views

Occupation detection using Face API [closed]

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 ...
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2answers
539 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 ...
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2answers
4k views

Which layer in a CNN consumes more training time: convolution layers or fully connected layers?

In a convolutional neural network, which layer consumes more training time: convolution layers or fully connected layers? We can take AlexNet architecture to understand this. I want to see the time ...
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1answer
3k 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 ...
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2answers
752 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 ...
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1answer
304 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
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1answer
63 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 ...
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1answer
60 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 ...
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1answer
121 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 ...
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0answers
67 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 ...
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1answer
47 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
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1answer
803 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 ...
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1answer
3k 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, ...
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1answer
73 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 ...
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2answers
157 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 ...
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2answers
229 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 ...
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1answer
183 views

In which scenario would you want to have two adjacent pooling layers?

In which scenario, when assembling a CNN, would you want to have two adjacent pooling layers, without a convolutional layer in between?
3
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1answer
1k 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-- ...
4
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1answer
99 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 ...
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0answers
203 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 ...
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2answers
179 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 ...
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1answer
365 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 ...
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0answers
30 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 ...
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0answers
75 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 ...
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0answers
78 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 ...
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1answer
682 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 ...
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4answers
831 views

What are the models that have the potential to replace neural networks in the near future?

Are there possible models that have the potential to replace neural networks in the near future? And do we even need that? What is the worst thing about using neural networks in terms of efficiency?
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1answer
83 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,...
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5answers
3k 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
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1answer
577 views

Regarding Yolo and Keras [closed]

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 ...
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1answer
156 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
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1answer
68 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, ...
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1answer
147 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
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3answers
356 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 ...
4
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3answers
984 views

Convolutional neural nets and reduction of the layers

I have a very simple question about Conv nets. I understand the whole principle, but only one thing is not well explained on the Internet. If I have a 16 channels image that goes on a convolutional ...
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4answers
142 views

What kind of neural network architecture do I use to classify images into one hundred thousand classes?

I have an image dataset where objects may belong to one of the hundred thousand classes. What kind of neural network architecture should I use in order to achieve this?
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2answers
2k views

What is the purpose of “reshaping it into the shape the network expects and scaling it so that all values are in the [0, 1] interval.”?

I am a deep learning beginner recently reading this book "Deep learning with Python", the example explains the process of implementing a greyscale image classification using MNIST in keras, in the ...
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1answer
609 views

How to load an image into tensorflow.js code which reads handwritten numbers and clasify them

I'm new to machine learning, so i figured I should look into google's tensor flow guides and I know how to code in JS so that's why I'm using tensorflow.js, there's and example in the guide that ...
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2answers
1k views

Speeding up CNN training

So I built a CNN without any scientific libraries like TensorFlow or Keras (only NumPy). It is taking a huge amount of time to train. What are some of the tricks and tips followed by people to speed ...
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0answers
80 views

Object recognition by two or more traits that are orthogonal (informally speaking)

I would really appreciate if someone could comment the following method of training neural nets providing them with some meta data (Making them more color prone only if needed, whereas now they're ...
2
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3answers
91 views

Which photo is more artistic?

I would like to develop a machine learning algorithm, given two photos, that can decide which image is more "artistic". I am thinking about somehow combining two images, giving it to a CNN, and get ...
3
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2answers
330 views

How to make a fair comparison of a convolutional neural network (cNN) vs a mutlilayer perceptron (MLP)?

I'm working with deep learning on some EEG data for classification, and I was wondering if there's any systematic/mathematical way to define the architecture of the networks, in order to compare their ...
4
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1answer
83 views

Relative compute time for each type of layer in a neural network

Hello, I would like to know whether this picture from the paper: Distributed Training of Deep Neural Networks: Theoretical and Practical Limits of Parallel Scalability valid? Questions: 1) Does ...
4
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2answers
2k views

What is feature embedding in the context of convolutional neural networks?

What are feature embeddings in the context of convolutional neural networks? Is it related to bottleneck features or feature vectors?
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1answer
53 views

Detecting Keypoint of 3D model, and distance between them

I am very new to AI, I have a set of 3D human models that I would like to train the algorithm to identify wrist, upper arm, lower arms, etc, and distance between them. From my understanding, this is ...
3
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1answer
2k views

Detecting license plate using tensorflow

I'm currently working on license plate recognition. My system consist of 2 stage: (1) License Plate region extraction & (2) License Plate region recognition. I'm doing (1) with Raspberry pi 3 ...
2
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1answer
954 views

Custom Object Detection model including orientation of the Object

I am looking to detect think objects like pens, pencils and surgical instruments. The bounding box is not important, but I am looking to see if I can train a model to detect both the object as well as ...