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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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Does CNN take care of zoom in images?

Suppose a convolution neural network is trained on small images of an object, say flower, as in following 3 training images: Will this CNN correctly classify if the same object is present in zoomed ...
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How can we use machine learning to distnguish between similarly looking images

How can I build a model which can distinguish between Milk and Phenyl? I want to predict whether a given item is edible to eat or not. If I train a model with thousands of photos of Milk and Phenyl ...
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convolution neural network:representing vector in fully connected layer

please i would like to ask about representing feature vector in the fully connected layer in cnn. i have image and i cropped it into N segments and fed each one into cnn branch and get feature maps ...
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58 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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Why is it possible to train a semantic segmentation neural network like U-net/Tiramisu from scratch using small data-set like few hundreds

Why is it possible to train a semantic segmentation neural network like U-net/Tiramisu from scratch using small dataset like few hundreds. While for the classification task, it is not possible to ...
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39 views

Why CNN and Neural network implementation not working properly

I am working on implementation of Bangla Handwriting Recognition From Scratch. The major steps involved are as follows: Reading the input image. each image shape ( 100,100,3) Number of Train ...
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Ubuntu OpenCV is not recognizing multiple faces using LBPH technique

I am working on facial recognition algorithms where I have developed the algorithm for recognizing 2 persons distinctively in OpenCV python on the windows operating system. That is working ...
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16 views

target and logits in the Mask-RCNN

I tried to implement the loss function in the mask-RCNN model using the Tensorflow tool. I used the average sigmoid cross entropy loss function: ...
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What is difference between intersection over union (IoU) and intersection over bounding box (IoBB)?

Can someone give a detailed explanation IoU and IoBB along with that the differences between them.
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Unbalanced training data for different classes

What precautions do I need to take while trying to develop a CNN for classification of images if there is much more training data for one label. For example: ...
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Magnification factor in image classification

If a CNN is trained on images focusing on an object, will it also recognize when multiple such objects are present in the image? For example can a network trained on single flower images also ...
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1answer
69 views

Detecting abnormal 'cat' behaviour via Supervised Learning

A few work colleagues and I were looking through a recently replaced 'cat', we had in the workplace. For those of you which are curious, the 'cat' in this context, refers to a specific type of pump ...
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What does the co-ordinate output in the yolo algorithm represent?

My question is similar to this topic. I was watching this lecture on bounding box prediction by Andrew Ng when I started thinking about output of yolo algorithm. Let's consider this example, We use ...
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Can we compile CoreML on Server?

I am working with CoreML and ARKit for Face recognition. But i don't want to build CoreML model with app. I have make a coreML model with python Turicate. I want this model to be put on server and it ...
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How to implement facial attendance system using less number of images of particulars

I have a project to implement facial Attendance where I have 5-6 images of particular and when individual comes, model should map the current image with person's earlier available images so if ...
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0answers
6 views

How to understand log-likelihood for generative image model?

I'm reading a paper on generative image modelling. In the paper, the authors compare various approaches by listing their "negative log-likelihoods" (see screenshot). What does this metric translate to ...
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1answer
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How to check two images(one is original image and other one captured by mobile) similarity using deep learning?

My problem statement is - In my project, original image of product is stored in database. Now whenever any person uploading that product's camera pic(for internal audit process) then I need to verify ...
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Applying a Convolutional Neural Network to Large Scale Satellite Imagery

I'm applying a Convolutional Neural Network (CNN) for semantic segmentation to map out habitats from satellite imagery. More specifically I'm using Mask-RCNN (paper and code) to a large scale ...
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1answer
22 views

System Requirements to train a Image Recognition Neural Network

I have 6000 Images to be trained on a Neural Network. My current PC Specs :- 32GB RAM, i5 2 core Processor, Standard GPU (No work going on GPU), 1TB Hard Disk My Neural Network Specs :- 3000 ...
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Cameras for automatic customer service machine [closed]

For my university project, I am planning to build an automated customer service machine. One which recognizes when someone approaches the camera according to says hello, etc. Also, I am planning to ...
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0answers
26 views

Better to crop or compress training data?

I've been trying to make an object recogniser in Tensorflow and have used labelImg to classify large electrical transmission towers at varying distances. In order to make 10-16MP (~2-7MB) images train ...
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Converting video into frames using openCV

I am converting video into video-frames using the given code converting video into frames ...
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1answer
36 views

Why is convolution filter used instead of correlation filter in CNN?

When I saw the two results of applying convolution filter and correlation filter, the results have the same distribution and are just flipped. Why is convolution filter used instead of correlation ...
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2answers
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Should we keep all channels when doing image classification?

I am discovering the world of image recognition and now trying to build an image classifier. The set of images I have have the shape (101,101,3) which means that it has 3 channels. If I'm not ...
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270 views

OSError: cannot identify image file <_io.BytesIO object at 0x7f5b2d2d9e60>

I created a lmdb dataset of images and labels but on reading the images, it is giving me error which I can't understand. Code: ...
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1answer
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Is it possible to make tensorflow print out everything it see in a given image and not just the top five results?

I'm working through the python API tutorials for Tensorflow and I'm seeing the results that are normally displayed, but it's always giving me the top five results. I'm trying to discern all ...
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2answers
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What is the loss function defined by Mnih and Hinton in their paper “Learning to Label Aerial Images from Noisy Data”?

In section 3.3 of the paper, they state that they use the cross entropy. Then they define the probability for a label to be a false positive as $\theta_0$ and a false negative as $\theta_1$. They use ...
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Where can I find a dataset of images of faces and descriptions of them?

I'm doing an ML project that generates descriptions of pictures of faces. Is there a publicly-available dataset that has a set of face images along with a short description of what the face looks like?...
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69 views

Machine Learning & Image Recognition: How to start?

I've been a full stack web developer for 15 years now and would like to be involved in machine learning. There is already a specific scenario for this: We have a database with several million products ...
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2answers
69 views

How to reduce the resolution of a Image(276*276 --> 48*48) without affecting the features in it

I have an image with resolution of $276*276$. I've created a Convolution Neural Network which accepts $48*48$ images. So, I want to resize that $276*276$ image to $48*48$ without reducing any features ...
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0answers
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advice on distance metric for knn w/image recognition

I'm getting my feet wet with machine learning and am implementing a knn algorithm on a dataset that i've created. I've created a set of images of circles and squares and want the knn algorithm to ...
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1answer
28 views

How can I split an image into rectangles?

I have a labelled form to which people will add their name and a series of numbers. They will then take a picture of the form. Like so: I can get decent results by simply sending this to AWS ...
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1answer
26 views

calculation of average ROC in IMageNet paper?

The IMageNEt paper Image Net. presents the Average ROC curve for the 16 classes in the imagenet data, visit image figure. 8 in the paper. what is the known function to compute this ROC plot. As ROC ...
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1answer
53 views

How Do Bayesian Methods in Machine Learning Help With the Problem of Limited Data? Can This Be Used for Image Classification/Recognition? [closed]

When reading about machine learning, I've often come across information stating that Bayesian methods in machine learning are effective when you only possess a limited amount of data. As someone who ...
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1answer
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Division of numbers from contours in opencv in python for cnn

I want to separate numbers in suppose 7638 into different images which can be predicted individually using cnn. By finding contours how can I divide each contour into separate image in python. To be ...
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1answer
38 views

Searching for a 3D Dataset, segmented by 2 or more Experts

We are looking for data sets with 3D images, preferably from the medical field. It is important that they have been segmented by more than one person/expert. An example of this is the BraTS Challenge ...
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39 views

Identifying computer scanned digits

I have digit images as below which I would like to identify: Some are of slightly worse quality : The images are not of a fixed resolution but are mostly in the range (80*20 to 130 *40). Due to ...
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1answer
110 views

How can you build a model that reads out receipts and invoices?

The objective is to build a model that is capable of identifying information on receipts and invoices that can look completely different. I've had a discussion with my brother about the right ...
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1answer
54 views

How do we predict what is in an image using unsupervised deep neural networks?

From my understanding of unsupervised DNNs for image classification: The input layer is a 4,096 dimension vector (for 64 x 64 images) The hidden layers represent much lower "features" as identified ...
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1answer
233 views

Detecting text region from an image

So I'm working on a document processing AI and I already have a character recognition model which performs decently well. Now the problem is, how do I feed each character to the model in order to make ...
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1answer
21 views

i need a characters /letters dataset for matlab

My final project is number plate recognition.i need a data set of A-Z characters and 0-9 letters. i donot find it on any website give me a data set or send me a link. i have to make a neural network ...
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3answers
1k views

Image resizing and padding for CNN

I want to train a CNN for image recognition. Images for training have not fixed size. I want the input size for the CNN to be 50x100 (height x width), for example. When I resize some small sized ...
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2answers
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Why would 2 sets of similar training samples take significantly longer to train?

I've built a fully-connected feed-forward neural network to recognize handwritten digits. I used MNIST and another very similar dataset (containing Arabic digits - same training set and test set count ...
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1answer
1k views

How does the bounding box regressor work in Fast R-CNN?

In the fast R-CNN paper (https://arxiv.org/abs/1504.08083) by Ross Girshick, the bounding box parameters are continuous variables. These values are predicted using regression method. Unlike other ...
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1answer
51 views

Image Matching to solve captcha

I am building a bot with python and I need some system to solve captchas like these: I think I need a deep learning algorithm, but coding one is a pain in the ass. Is there any easy solution to this? ...
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1answer
56 views

Is color information only extracted in the first input layer of a convolutional neural network?

In a convolutional neural network (CNN), since the RGB values get multiplied in the first convolutional layer, does this mean that color is essentially only extracted in the very first layer? ...
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1answer
48 views

Is there an AI service that could be used to classify 30,000 different tools and parts?

I'm trying to build an image classifier where people can take a picture of a tool or part and have the image classified. Much like bixby or amazon's tool to do something similar, but with only 30,000 ...
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2answers
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In a convolutional neural network (CNN), when convolving the image, is the operation used the dot product or the sum of element-wise multiplication?

The example below is taken from the lectures in deeplearning.ai shows that the result is the sum of the element-by-element product (or "element-wise multiplication". The red numbers represent the ...
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1answer
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Could we use image hasing techniques for images classification tasks?

I have read some articles about image hashing, and I would like to know if we could apply this technique for general purpose images classification tasks. Especially I would like to know which could ...
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2answers
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How can I find out what class each of the columns in the probabilities output correspond to using Keras for a multi-class classification problem?

I'm using transfer learning to build an image recognition model using a pre-trained VGG network in Keras and excluding the final fully-connected layer to get the output weights. I'm then using these ...