Questions tagged [image-classification]

For questions about image classification: a decision problem where an algorithm must decide to which class ('cat', 'chair', 'tree') an input image belongs.

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Best Model for Multi-label image classification

Usually using CNN architecture with a Sigmoid function as an activation function in the last layer and using binary cross entropy can be used to output a probability for each class. However, the ...
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Is there is exists dataset contains images labels/classes from some social network like Instagram? [closed]

I'm doing a recommender for one social network disabled yet. Social network includes images post, like in Instagram. My idea is scrap images labels/classes and then try to classify it in some given ...
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Transfer Deep Learning from one aerial imagery datset to many others

I am new to Deep Learning but have been able to use RasterVision successfully to predict building footprints within a set of aerial imagery. This aerial imagery data set is for a province of New ...
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dataset split for image classification

I am trying to do image classification for 14 categories (around 1000 images for each cat). And i initially created two folders for training and validation. In this case, do I still need to set a ...
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How to convert classification maps to bounding box

I have a fully convolutional network that has been trained to classify cats and non-cats in small images (48x48). Because it is fully convolutional, I would expect that if I run it in bigger images, ...
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How to find out what portions of an image is helping CNN to classify it

I am working on an image classification problem using Transfer learning. Right now, I am getting an accuracy of 75% on train data and 67% in test data. Now I want to understand what portions/parts of ...
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Precision or Recall when dealing with critical cases?

I have to create an AI that classifies mutliple objects in order to accept them or not inside a machine. The problem is that some objects could be really harmful to the machine if they get accepted. ...
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best similarity measure for images with different angles

I want to compare different images (where the images are of the same setup but the angles with which the images are taken are different). I want to obtain some sort of similarity score. I tried using ...
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Difference in threshold values for DBSCAN and Threshold clustering

I am trying to cluster similar faces using Facenet embedding approach. I am extracting a 256 feature vector using Facenet model on a standardized labelled Celeb-faces dataset, and trying cluster using ...
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Labelling Images - Image Recognition

I'm new to image recognition and I've been tasked with implementing a YOLO classifier. Images I have relate to the installation of a product. So to train this custom dataset, I've been labelling the ...
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1answer
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Max Pooling in first Layer of CNN

I am seeing, in all the notebooks that I found, that Max Pooling is never used in the first layer of a CNN. Why this? Is it a convention among data scientist to do not use max pooling in the first ...
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How to deal with a small dataset for image classification using CNN?

I have a dataset consisting of characters(lowercase and uppercase) and numbers, totalling about 62 classes. The data I have are about 45 images per class and no test data. The data is a subset of the ...
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Find starting point and stopping point of noisy pulse

I have noised pulse signal like these. I need to identify starting point and stopping point of each peak. First and third pictures have 2 pulses with noise. Second picture has single pulse with noise. ...
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1answer
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Approach to labelling new data for training

Overview: Imagine an application that identifies cats and dogs from their phone camera. User's take a photo of their pet and it tells them if it is a dog or a cat. The data is then sent to the server. ...
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Image classification vs medical grading problems

For image classification problems like cat vs dogs, the output layer is 2. Image classification problems like diabetic retinopathy seem to be more of a grading classifier. Although the targets range ...
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CNN Model Seems To Just Be Guessing

I am working with a binary classification problem, and regardless of what changes I make, the model seems to just be guessing between 0 (Negative) and 1 (Positive). The dataset is imbalanced at a ...
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How to train a deep neural network with time-series images and unbalanced dataset?

I have images that represent a fixed-length time-window of different serials. Serials have time-series of different size, so e.g. serial1 has length 30, serial2 length 110 and so on. I have multiple ...
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14 views

Image Embeddings Layer with Pre-Trained Model

I have some basic experience with embedding layers in NLP. However I would like to explore how can I use embedding layers to compare similarities between images. There are a few questions I am stuck ...
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How to write decider function for multiple models

I have trained two classifiers .. Text Classification and Image Classification. So both models gives score for each class. For example there are 3 classes. Each model give array of 3 confidence score ...
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Validation Accuracy not going beyond 60% for image classification with 5 species of snake

My dataset has about 17000 images belonging to 5 classes. I am using 16000+ images for training(about 3k/class) & 500 for validation(100/class). Training accuracy is very good but validation ...
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How do we know that model learned those features from the image dataset in deep learning?

I am implementing image classification using TensorFlow.How do we know that model learned those features from the image dataset in deep learning. can we visualize that?
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CreateML mlModel fails to infer a few classes

I have a Image Classification problem (black and white stick figures) The issue is that two classes never get inferred. The training dataset has 500 classes with 100 or more (299x299,1) samples per ...
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Classification with Orange error “test and train datasets have differents target variable”

m having a problem on the widget "Test and score" used for classification. Im doing a classification on images and i would like to use the widget "test and score" with the option &...
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1answer
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ship class Object detection with custom model weights

I have made a model to classify different categories of ships(yacht,catamaran,rubber boat) in Python and i hit a 70% accuracy in training so now i have my weights.hdf5 file.Now i need to object ...
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1answer
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is this problem a multiclass case?

I'm trying to classify my textile design patterns (let's just think of it as medieval painting) what I understand of "multilabel classification" is like this: it outputs multiple possible ...
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1answer
38 views

Input shape of an Xception CNN model

I have a Keras Xception based model for gesture recognition. The accuracy of the model is around 60-70% for classifying 7 different gestures. The training dataset consists of 320x240 and 640x480 pixel ...
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Use Tfrecord to feed multi-input neural network

I have a dataset on Tfrecord that includes images and tabular data, I want to feed those data into a mixed neural network data. I saw examples of how to use multi-input neural network by using numpy ...
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1answer
26 views

Why is my CNN not training

Hi I am trying to train a CNN to differentiate between pictures of dogs and pictures of cats. It does not seem to learn anything no matter how I change the architecture. I have used the following code ...
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Looking for more recent dataset for document classfication

I am trying to develop an NLP - CNN algorithm to detect documents with sensitive information such as passport, license and distinguish them from other documents like resume, email, form or ...
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How many images are generated when ImageDataGenerator is used, and when data augmentation is included as a part of the model?

Is there any way to know the number of images generated by the ImageDataGenerator class and loading data using flow_from_directory method? I searched everywhere for the same but couldn't find anything ...
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How to append new image to train with existing image classification TensorFlow model?

I have 10 classes of images. Let's say 1 class has 500 images after training the model I want to add extra 100 images to the existing class. After adding extra images should I retrain all images 500 +...
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1answer
39 views

What features used by CNN model should a feature store actually store? [closed]

According to MLOPs principle, it is recommended to have a feature store. The question is in the context of doing image classification using deep learning models like convolutional neural networks ...
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2answers
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What are the activation functions in Convolutional Layers for?

I read a lot about CNNs but I didn't quite understand some things: What are the activation function in CLayers for? If I understood it right, the only weights in these layers are the ones in Filters, ...
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Accuracy mismatch in tensorflow model

I am working on image classification project. I have trained model on car dataset. So it gives good accuracy but when I predict BMW car with my model it gives below results. BMW :- 98% Audi :- 91% Why ...
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1answer
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Machine learning classification with time-domain signals how to ignore signal arrival time?

I am training a Tensorflow classifier model with signal data (converting signals to the spectrograms). I want the model to be insensitive to the arrival time of the signal within the fixed window. ...
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37 views

Nutritional image classification task

I need a model that is able to receive as input an image of a nutritional information chart and tell the level of sugar that the product has. It would be a 3-class classification problem (low if sugar ...
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272 views

ValueError: Input 0 of layer conv1_pad is incompatible with the layer: expected ndim=4, found ndim=3. Full shape received: [None, 224, 3]

I am trying to make a gender classifier. I am using MobileNet from Tensorflow with input shape as (224,224,3). After training the model, I tried to check if the model was working by passing an image ...
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Close set and open set classification at the same time

Is it possible to use a neural network(or another approach) to classify image based on trained data and at the same time if new image classes are introduced in the test set it should classify those ...
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Multiple input image per subject

Sorry for the newbie question. I have 40 labels/subjects 20 diseased and 20 normals. All the 40 patients have 3d images. I want to run a classification task using 3D-CNN with multiple 3D MRI images. ...
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Denoising Prior to Image Classification

From what I have read, Denoising during preprocessing for image classification tasks seems to be a bit controversial. While on one hand it might improve classification accuracy, the computational ...
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2answers
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What is the use of using width/height shift in data augmentation?

I'm not sure to understand the use of augmentation data using width shift and height shift. Say I have limited image data, and I want to create new data using Keras' ImageDataGenerator. To classify ...
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Mask RCNN 1 class only

I am looking to use only one class, person (along with BG, background), for the Mask RCNN object detection. I am using this link: https://github.com/matterport/Mask_RCNN to run the mask rcnn. Is ...
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Detect photos of boats which have the Europe's flag installed on it

My task is a binary classification: is there a boat in the picture that has the Europe flag installed on it? In other words, my classifier should first detect if there is a boat in the picture or not, ...
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1answer
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Negative Feedback to GradCam method

I use EfficientNetB0 for performing image classification with one of the class as "stone countertop table", the other class is "not stone countertop table". I use the reddest part ...
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1answer
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Can a trained recognition model be used to generate a sample?

Suppose we have trained a cat classification network. It takes in an image (as a vector) x and returns $\hat{y}\in(0,1)$. The loss function is the typical cross entropy function. Shouldn't it be ...
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Suggestions for Open-Source Tool for Image Classifications (with Nesting)

I'm looking for an open source tool to assist my colleagues and I to label images for a machine learning application. We don't actually need bounding boxes or anything to pinpoint regions within each ...
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predict multiple letters in pixels matrix

I have a multilayer perceptron model that is trained to recognize handwritten English letters from an image. In the training set each image matrix had 784 pixel values. The labels of these images ...
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Large general-purpose model vs ensemble of many smaller models

I am reading this paper - https://arxiv.org/abs/1503.02531v1 - devoted to knowledge distillation in neural networks. One interesting approach is mentioned in this paper in sections ...
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1answer
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How would you build a big production ready image training dataset from scratch?

How would you most likely create a large production ready image training dataset from scratch including annotations for a image classification task? We will take a large amount of images (~1 million) ...
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Will images modification get me a better machine learning model?

Will images modification get me a better machine learning model? I have the following scenario. Camera is fixed and does photos of a process. The process has a few states. Now I want to train a model ...

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