Questions tagged [image-recognition]

A form of signal processing where the input is an image. Usually treating the digital image as a two-dimensional signal (or multidimensional). This processing may include image restoration and enhancement (in particular, pattern recognition and projection).

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13 views

How do I identify specific parts of a PDF document?

I have a bunch of medical records that I have to input manually. I would like to automate this but all of the records are in different formats. What is the best strategy to build a deep learning model ...
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Why is a general/original softmax loss not preferred in FR (face recognition)?

In some papers I've read that softmax loss is not preferred in FR since it does not give a good inter-class and intra-class margins, but could not understand 'why?'. So can someone explain, why ...
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Selfie image embeddings

https://arxiv.org/pdf/1906.02940.pdf I have read an article and want to implement an embedding algorithm. My problem is that I do not fully understand how the classifier is built in the decoder. More ...
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Can Microsoft's cognitive service find similar person in a set of images without using the face service?

I need to create an application that can detect if a person X entered as an input exists in an image set and return as output all the images in which the person X exists. The problem is that the ...
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How and Why to rescale image range between [0,1] and [-1,1]

I am trying to implement model described in Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network in which author says in section 3.2 that We scaled the range of the ...
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39 views

Super Resolution CNN vs Regular CNN

I am digging into finding a solution for background subtraction and one of the requirements is to not loose in quality of input image. Found that there is a specific type of CNN like Super Resolution ...
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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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Training a CNN to convert ellipses into circles

My current project has to do with modeling the effects of blurring/convolution of objects in various imaging processes. Right now, I am starting off with a preliminary, artificial model. I am using ...
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How to train or approach the image datasets with different resolution in Deep Learning

Image classification: I am having a data set of image collection more than 10k but even though all are the same image but taken in different sizes (pixels into pixels) some are in square and some are ...
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Storing masks in jpg format

I've created masks(numpy array with 0,1 as values) and tried exporting this array to jpg using matplolib but it's not exporting the values as it is. I'm getting a range of pixel values in resulting ...
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Unsupervised learning for image treatement

I'm searching for methods that I can use to detect objects in images using unsupervised Learning. I found that the CNN and AE can be used , but I'm not sure. Anyone can guide me please
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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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Have you come across a dummy passport or drivers license dataset for training models?

We've built a new public benefits screening application that can recognize passports, drivers licenses etc from scanned images, used for people to prove identity when applying for government benefits, ...
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Best OCR approach on documents with different formats to find one specific information

Unfortunately, because of confidential data, I can't give a more specific explanation. The Problem So I've got a few documents that in general contain the same information but have different formats....
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Is text recognition by definition a part of image recognition?

I'm referring to more advanced text recognition systems that are using neural networks to find and extract text from images like the ones Google and Microsoft are offering on their ML platforms. If ...
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Semantic Segmentation using Scipy or Scikit-image

Many days ago I saw a user using scipy function to get region of interest (RoI) in an image using different colors. I believe it was some sort of filter. Now I'm trying to do the same but I'm not able ...
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Feedback on duplicate and near-duplicate image detection

Good morning all, I recently completed building a script that does the following: Stores a list of all .jpg images existing in specified drive. Cleans/ids duplicates through md5sum Iterates ...
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Why do we use a softmax activation function in Convolutional Autoencoders?

I have been working on an image segmentation project where I have created a convolutional autoencoder. I saw this image and implemented it using Keras. At the output layer, the author has used the ...
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Why some papers writing false positive rate per case instead of percentage rate?

In some published works specially in medical image analysis, instead of writing FP rate as percentage, they write it per case, for example: FP: 128.52 [/case]. What is the meaning of this? Is it have ...
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Extract text from a image - OCR

This is the first time I am working with OCR. I have an image and want to extract data from the image. My image looks like this: I want to extract the parameters and the values against them. Can ...
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In which publication was the term “Dimension-Hopping” coined?

Apparently Geoff Hinton coined the term but was it through literature or lecture? I just want to add a reference for using the term in my report. Dimension-Hopping in Machine Learning
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Why do most published works in medical imaging try to reduce false positives?

In medical image processing most of the published works try to reduce false positive rate (FPR) while in reality false negatives are more dangerous than false positives. What is the rationale behind ...
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Analyzing multispectral images data from a drone

We are planning to develop an application/software for monitoring of rice field. After researching, I was curious on how to analyze the data from drone camera. Reading the data and then showing the ...
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tfrecord file size larger than the original data size and how to reduce this size?

tfrecord file size larger than the original data(video-frames) size. Is there any way to compress or reduce tfrecord file size. Do you have any suggestions or ideas?
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Pre trained neural networks to recognize certain things

How do you approach the problem or is not classification? For example, I would like to recognize if a face has makeup. But, in order to do this, it would first need to be able to recognize if it is a ...
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How to locate the invoice within a camera captured image?

The demand is to locate the invoice within a camera captured image about that invoice. The invoice is always a white paper with printed black or blue characters, tables and red stamps. Sometimes the ...
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30 views

Data set of vectors of SVG paths for digits

I have used the MNIST data set many times to train models for digit recognition based on object character recognition (OCR). I am now trying to do the same but with a data set of svg paths.. I am ...
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State of the art in accurate object tracking & detection

Im working with an offline video file which has vehicles in it. I tried using YOLOv3, but it is not very accurate. Moreover, it kind of fails in occlusion. I am concerned more about accuracy than ...
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Facial Recognition Using One shot Learning Research Paper

1) I am looking for a latest Research Paper for "Facial Recognition Using One shot Learning" for my semester Project. I want to implement that paper and want to improve that. i have searched on ...
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How can one quickly look up people from a large database?

Vocabulary Face detection: Finding all faces in an image. Face representation: The simplest way to represent a face is as an image (pixels / color values). This is not very space efficient and likely ...
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1answer
121 views

How to encode a time series as an image to feed it into CNN?

I want to try CNN in the task of stock chart pattern recognition. I suspect that feeding a line chart won't work because the image will have a lot of empty pixels. What time series encoding options ...
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Is it possible to make a 'forked path' neural network?

I want to make a network, specifically a CNN for image recognition, that takes an input, processes it the same way for several layers, and then at some point splits before coming to two different ...
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65 views

YOLO: What is better? multiple networks per label or multiple labels in single network?

I would like to use a YOLOv3 network,load in the preexisting trained weights, then retrain the ending layer to recognize say, 20 labels. Would adding labels to a single network in training reduce its ...
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What is the difference between “offline trained model” and “pretrained model”?

I am confused that both are same or not, and then how can I differentiate with the online training model.
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getting the weights of intermediate layer in keras

I have an image dataset 376 classes each class has 15 pictures corresponds to a person. I would like to get the feature vector that corresponds to each person. What I have done is, after I compiled ...
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Learning image embddings for clustering based on custom distance metric

I have a large dataset of images, and i can calculate their distance to oneanother. I will at a later point recieve new images where i can not determine their distances to the ones in my training set(...
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How can I detect partially obscured objects using Python?

I'm building a computer vision application using Python (OpenCV, keras-retinanet, tensorflow) which requires detecting an object and then counting how many objects are behind that front object. So, ...
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Image Matching for similar products

Is it technically possible to find out similar products online based on an given image? Say the first link is a hoodie for women selling on Amazon. I want to do two things. Based on the image, I ...
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Mask RCNN detecting object but mask is inaccurate

I am trying to detect the inner region of a object. Currently I am using the mask rcnn implementation provided by tensorflow in the models zoo. The object is similar to a hula hoop that is square in ...
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Encoder Decoder Network Image Compression

Could you train an encoder decoder network to take an image in and attempt to recreate that image as an output. I am basically interested at looking at the intermediate feature vector representation ...
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Matching a book spine image against a database of images

I am working on a problem related to book identification in a library. For this I have to match a book spine image (query image) against a database of book spines and find the best match so that I can ...
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Image Classification on non real images

I was wondering how image classifier networks perform on images that are not photographs. For example if you were to feed a drawing of a car or a face to an image classifier that was only trained on ...
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Image preprocessing: How to resize / align / cut images of various sizes?

I want to create a new dataset for image recognition. If I have Object A that I want to recognize in images, and multiple images of various different sizes, how do I preprocess them so that they ...
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CNN strategy in recognizing spinned images

I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels ...
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How can I train a model for localizing objects(classification not required) in Python

I need to make a model that creates bounding box around objects(but does not classify them) for a competition. Which libraries or pre-trained models should I use. I need values of x1,x2(x1+w),y1,y2(y1+...
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Implementation of Siamese network

What would be the ideal ratio of positive, negative image pairs, and the number of image pairs to classify if two images are of same person in Siamese network ?
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Where/How to start? [closed]

I want to create an application that recognises diseases from images, I know this require databases of images and image segmentation but where do I start? What should I start learning? I know nothing ...
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Useful metrics to compare network-output image to true image?

I'm designing a supervised network that would require to output an image. I'm wondering what are the best metrics to find similarity between the output and actual target image. So far, my best ...
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Recognition of objects in almost plain background

I want to recognize climbing holds in a climbing wall. I thought about implementing my own heuristic algorithm for background detection because it's almost plain, but I was wondering if this kind of ...