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Questions tagged [computer-vision]

Computer Vision is a subfield of computer science which deals with analyzing and understanding images. This includes detection of objects like faces in images or segmenting images.

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Keypoint matching using HoG and SIFT

I have two images and I've found their keypoints using sift keypoint detector, Now I have to match their keypoints with HoG features, I know how to extract HoG description, but I dont know how to ...
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54 views

Using tensorflow object detection in another model

I am trying to use Tensorflow (tf) object detection API models in another custom model I built. Specifically, I am trying to do: jointly train tf object detection models Y with another model X. in a ...
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1answer
412 views

MR images segmentation for feature extraction

I have datasets of brain MR images with tumours, the tumours are already selected manually by a physicist using Image J. I have read about segmentation, but I still couldn't understand how do they ...
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1answer
35 views

Feature selection/reduction technique for combination of features in image processing [closed]

I have a combination of features extracted from 3 descriptors. Namely, GLCM based features (correlation, homogeneity, energy, and contrast ), Local binary patterns (256), and discrete wavelet ...
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0answers
166 views

segmentation of brain tumor in MRI images

I have a dataset of brain tumours images. and I have to build a model to classify the malignancy grade of these tumours. The size of the tumours varies from small to large. The ROI are already ...
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1answer
4k views

cross validation for small dataset

I have a dataset of 39 medical MR images, and I have to build a model to classify the tumor type. so is it suitable to use k-fold cross validation for validating the model? if so, what would be the ...
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1answer
49 views

How would you a apply a cnn to do age estimation on static images? [closed]

After doing some reading on age estimation using the IMDB wiki dataset I wanted to try it out myself on a smaller scale but I dont quite understand the application of the CNN. Any clarification would ...
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2answers
25 views

Autonomous evalution

Do you think it is possible to learn the app, how to autonomous evaluate good or bad parking of the bikes? The thing is you need to take a picture with your phone and app need to decide according to ...
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2answers
335 views

Equivariance vs Invariance in Convolutional Neural Networks

Could someone please explain to me in details (possibly from mathematical point of view) what is the role of Equivariance and Invariance in Convolutional Neural Networks, and how are they actually ...
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0answers
109 views

OCR on striked-out text

I have the following image with me: I want to identify the text, which is the amount mentioned at the bottom of the table. However, the bottom edge of the table goes through the text in this case. ...
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0answers
40 views

How can I get the original pixels that lead to the decision in CNN?

I work on medical images and I want to locate the most relevant regions of the image based on deep learning spatially CNN. So I feed my data into VGG16 architecture and get the features maps. Now I ...
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1answer
171 views

YOLO pretraining

I'm implementing YOLO network and have some questions. In the original paper the authors say: "For pretraining we use the first 20 convolutional layers from Figure 3 followed by a average-pooling ...
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0answers
398 views

Training detector without bounding box data

From what I can see most object detection NNs (Fast(er) R-CNN, YOLO etc) are trained on data including bounding boxes indicating where in the picture the objects are localized. Is there any model ...
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2answers
330 views

YOLO layers size

According to the original paper, the input size of the YOLO network layer is 448x448x3 and after the filter (7x7x64-s-2) is applied the output shape is to be 221x221x192 as I suppose. Some sources ...
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1answer
509 views

Bounding box coordinates prediction

How to pass multiple bounding boxes coordinates to CNN model?My goal is to predict the coordinates of texts in an image.
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0answers
756 views

Examples for multi-input Convolutional Neural Network

I want to create a multi inputs Convolutional Neural Network (cnn) that takes two inputs and produces one output of the inputs class by using Keras. I searched for resources that explain multi inputs ...
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1answer
2k views

How to visualize image segmentation results

I am using u-net to do semantic segmentation for N>1 classes. The input size is (128,128,3), the output size will be (128,128,N). what is the correct way see the prediction as an image ot size n1 x n2 ...
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1answer
46 views

What exactly does the model generation mean in this diagram?

I've been trying to grasp a research paper on image colorization using neural networks here I am stuck at this diagram. What I need help on, is the Model Generation step after Feature extraction. ...
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2answers
4k views

Bounding Boxes in YOLO Model

The YOLO model splits the image into smaller boxes and each box is responsible for predicting 5 bounding boxes. My question is how does the model make these bounding boxes for every grid cell ? Does ...
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0answers
95 views

Convolutional neural network for gray images

I am using vgg16 to design a CNN that takes gray input images. The model give me good results without changing anything related to colors. I am not sure if what I did is correct or not. I want to ...
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0answers
33 views

Deep Learning ROC and Average Precision Curve Results

I used Vgg16 to create a deep learning model and the dataset is imbalanced so, I used class_weight argument in fit_generator method. The model result as the following: accuracy= 98.9% and loss= 0....
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2answers
4k views

How to properly save and load an intermediate model in Keras?

I'm working with a model that involves 3 stages of 'nesting' of models in Keras. Conceptually the first is a transfer learning CNN model, for example MobileNetV2. (Model 1) This is then wrapped by a ...
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0answers
109 views

it is possible to use features maps of CNN to localised important areas in image?

I'm new in deep learning and CNN, I understand how convolutional and pooling layers work, I understand how and why feature maps are created. How I can localize from the feature maps important area in ...
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1answer
9k views

How to make two parallel convolutional neural networks in Keras?

I created two convolutional neural networks (CNN), and I want to make these networks work in parallel. Each network takes different type of images and they join in the last fully connected layer. ...
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1answer
111 views

How to fetch text from pdf to further proceed with question answer based model from the same document?

To illustrate the above title. Suppose you have a pdf document, which is basically scanned from hardcopy, now there are set of fixed questions to answer from the document itself. For an example a ...
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1answer
2k views

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 ...
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2answers
2k views

Overfitting in Siamese Network

I am trying to train a Siamese network for an application very similar to this and this. From what I have read about training Siamese networks dissimilar pairs of images outnumber the similar pairs ...
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1answer
3k views

Semantic segmentation: mean IOU in presence of missing classes

It seems to me that the mean IOU is a poor metric in the presence of unbalanced classes. E.g., suppose I have 10 classes but one image has only 2 classes present in its label. Consider the prediction ...
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1answer
112 views

Getting rid of maxpooling layer causes running cuda out memory error pytorch

Video card: gtx1070ti 8Gb, batchsize 64. I had such UNET with resnet152 as encoder wich worket pretty fine: ...
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0answers
1k views

Cross validation for convolutional neural network

I am using Keras to create a CNN model, and I would to use K-fold cross-validation to train the dataset. The dataset contains images and I am using ...
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2answers
2k views

What is the difference between using numpy array images and using images files in deep learning?

What is the difference between using numpy array images and using images files in deep learning? Which way is better?
2
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1answer
746 views

Should I use rescale parameters for data augmentation? [closed]

I am using Keras library to build a CNN model. I want to use data augmentation for training data. Should I use rescale parameters for data augmentation? ...
5
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1answer
325 views

Data augmentation parameters

When I use data augmentation to increase the train dataset, should I use all augmentation techniques (parameters in keras)? Which data augmentation parameters should use with ...
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1answer
15k views

Optimizer for Convolutional neural network

What is the best optimizer for Convolutional neural network (CNN)? Can I use RMSProp for CNN or only for RNN?
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1answer
976 views

Data augmentation in deep learning

I am working on a deep learning project for face recognition. I am using the pre-trained model VGG16. The dataset has around 100 classes, and each class have 80 images. I split the dataset 60% ...
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2answers
3k views

Data augmentation: ImageDataGenerator vs openCV

I would like to increase the data in my dataset to create a CNN deep learning classification model. Which is better for the model, using data augmentation by ...
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2answers
145 views

Neural Network Architecture for Identifying Image Copies

I have a large image collection and wish to identify the images within that collection that appear to copy other images from the collection. To give you a sense of the kinds of image pairs that I ...
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1answer
2k views

Resnet 50 as a backbone of Unet

I want to use a pre trained Resnet 50 as a backbone for Unet model. But the issue is resnet 50 is expecting the size of image as 197 x 197 3D channel but the image of mine is 128 X 128 x 1D channel. ...
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4answers
635 views

Image recognition of selfie images

I developed an Android app that lets anyone upload pictures of encyclopedic things (bridges, museums, dishes, landscapes, paintings, etc) to Wikimedia Commons. Unfortunately, 5% of the users find it ...
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2answers
573 views

How to determine the number of the training images in Keras after data augmentaion?

I want to create a CNN model and I am using data augmentation. I want know the number of augmented images in Keras. How to determine the number of the training images in Keras after data augmentation?...
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4answers
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Classification problem with many images per instance

I am working in the following kind of classification problem: I have to classify every instance as class A or class B using many images of the instance. That is, every training example has not one ...
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1answer
2k views

How design a autoencoder architecture

I would like to build an autoencoder (CNN) to learn a representation of my data. I never built such a network and I have some experience in supervised learning (classification). I would like to know ...
3
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1answer
80 views

Classifying Car Data By Year

I have huge car photos. I want to predict car's "brand-model-body type and production year" First, I splitted data into train and validation, and I categorized them like this. Every category has ...
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1answer
4k views

Multiple keras models parallel - time efficient

I am trying to load two different keras models in parallel. I tried to use the functional API model: ...
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0answers
44 views

Best practices to modelize top layers over CNN

I'm fine-tuning a InceptionResnetv2 network to get a features extractor, so I'm training a classical classifier with my data (one label/data, i'm using a softmax). I would like to know how to choose ...
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1answer
101 views

Effective Methods for Background Removal on Images

I'm interested in learning about how background removal works on images taken of clothing items. Do we need a specific color difference between the background and the clothing item in order to be able ...
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2answers
987 views

Meaning of dropout

What does model.add(Dropout(0.4)) mean in Keras? Does it mean ignoring 40% of the neurons in the Neural Network? OR Does it mean ignoring the neurons that give ...
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0answers
173 views

Maximum number of classes YOLO net can recognize

I'm trying to make a mobile app on image recognition(Computer Vision Application) . Does anyone know whether modern day smartphones have enough processing power/memory to recognize, say about 1 ...
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2answers
169 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 example An image of a dining table ...
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2answers
2k views

ValueError in CNN+RNN model in keras

I am trying to build a CNN+RNN model for a computer vision problem. below is my code ...

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