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.

Filter by
Sorted by
Tagged with
1
vote
0answers
12 views

Can reducing the number of classes in multi-label classification increase performance?

This is more of an open question with people which have experience in this. I'm working on a multi-class multi-label classification for chest x-rays. I would like to know how much can reducing the ...
0
votes
0answers
6 views

Unrelated output by pytesseract image_to_string function

I'm trying to extract text from an image but pytesseract is giving a totally different output, the image attached below output is "Werle" (complete different word and characters), I tried ...
-1
votes
0answers
10 views

How to manually collect rectangular training data samples from images? [closed]

I want to collect training samples from images. That can mean different things depending on the context. I think of the simplest case, which should be most commonly required. Because it is so common, ...
0
votes
1answer
19 views

Pre-trained CNN model makes Poor Predictions on Test Images Dataset

I have tried using several a pretrained models (MobileNet) for multiclass predictions. There are 42 classes and the distributions of the images are even across the 42 classes. This is my code: ...
1
vote
0answers
24 views

Classification of moving pixels with convolutional neural networks

I have a data set with videos of moving pixels. Each video contains 32 frames, each frame is 32x32 with two pixels in white and the rest in black. I have binary labels for 800 of these obtained by ...
1
vote
1answer
12 views

Separating styles of numbers for simple digit classification

I am just getting started with my first simple digit classifier, so my doubts are at a pretty low level. In every dataset of digit images I've seen so far, different variants of each digit are grouped ...
1
vote
2answers
31 views

Why my training and testing set are about 99% but my single prediction does wrong prediction?

I have performed fruits classification using CNN but i am paused at a point where all things are going right confusion matrix accuracy score all are correct it seems there is no overfitting but it ...
0
votes
0answers
10 views

Train using the raw pixel images or training using facial embeddings

I want to create a model that can classify faces based on these face shapes(oval, square and heart). When creating my CNN model should I train it using the images as they are or should i generate the ...
0
votes
1answer
14 views

Should augmentation also be performed on the validation set when the dataset is imbalanced?

I am training a CNN on images (2 classes) and I have an imbalanced dataset (1:7 ratio). I am trying to tackle this by performing offline image augmentation. Should I perform augmentation also on the ...
0
votes
2answers
17 views

MNIST data shape

In going through the different tutorials on CNN, auto encoders and so on I trained my self on the MNIST problem. The different images are stored in a 3D array which shape is (60000,28,28). In some ...
1
vote
1answer
17 views

Image classification using cnn [closed]

I did image classification using CNN and it successfully classified the images but How to save predicted images to separate folder for example i have two classes cat and dog after prediction how to ...
1
vote
1answer
17 views

ANN Classifier for extracted discrete image features

I have a features extraction algorithm that works well to extract features from images. I want to develop an ANN to classify those images based on those features. I have extracted features in a csv ...
0
votes
1answer
13 views

Why does the model make good predictions for augmented images and not for the original ones?

I am training a CNN using maps images and I have performed offline augmentation operations (FLIP_LEFT_RIGHT, FLIP_TOP_BOTTOM, ROTATE_90, ROTATE_180, ROTATE_270, TRANSPOSE, TRANSVERSE) on the whole ...
0
votes
2answers
27 views

What to input into machine learning algorithm for image recogniton?

I am working on a project that involves classifying images as either that of a cat or that of a dog, without using CNNs. I used SKImage to convert the images to a matrices and changed it to grayscale ...
0
votes
2answers
33 views

How to convert images (.jpg) to vectors for image classification

I'm currently working on a project that involves classifying an image as either that of a dog or that of a cat. The twist is that I want to do this without using Convolutional Neural Networks, mainly ...
0
votes
0answers
14 views

Object identifaction with trained CV model

I am rather new to Computer Vision and Neural Networks, but I already build the following setup: I have a robot which crawls through the grass with a live video feed. I build an OpenCV filtering and ...
0
votes
0answers
32 views

Ways to visualize the outcome of machine learning interpretability techniques (for image classification)

“Machine Learning Interpretability” or “Explainable Artificial Intelligence” has become quite popular in the machine learning community and in recent research. The goal is to make complex (deep ...
0
votes
1answer
18 views

build biased image dataset for emotion analysis

This is a pre-project question. I would like to find or build a biased dataset to demonstrate what happens if training data are biased (biased distributed ethnicity for exemple). I try this for the ...
-1
votes
0answers
18 views

Machine Learning: Dataset and Labelling for detecting an object on a human's face

I'm a beginner in machine learning and am attempting to train an AI to recognize if a person in a photo is wearing a face mask or not. I am using python (Tensorflow 1.X), SSDLite with Mobilenet v3 ...
1
vote
1answer
27 views

Can I train a CNN to detect the number of objects without localizing them first?

So I was trying to search but couldn't find any answers. I was wondering if it possible to train a model to detect the number of items of interest in a photo without having bounding boxes or dots to ...
2
votes
1answer
25 views

Weighted loss functions vs weighted sampling?

For image classification tasks, is there a practical difference between using weighted loss functions vs. using weighted sampling? (I would appreciate theoretical arguments, experience or published ...
0
votes
0answers
11 views

Creating custom datagenerator in Keras with variable input size

I am currently working on an image classification problem. Each label that I have is determined from 4 grayscale images of variable size (ranging from 30px to 300px in height and width). Hence, I ...
0
votes
0answers
22 views

Problem with data augmentation only on train set!

So I want to augment my data but unfortunately, I don't have an individual folder for train and validation set, and of course, I want to only augment the train set but if I use this: ...
0
votes
1answer
25 views

Keras Model Predict is not predicting all images flowing from directory?

I have the following code where I have done all the training and passed the testing set as a flow from directory. After that when I pass that object into the model.predict option, the array received ...
1
vote
0answers
27 views

List of undesirable faces?

An Australian sporting league simulated live crowds using cardboard cut-outs to fill empty stadiums during COVID-19. Fans were allowed to submit their own faces to be used on the cutouts, which ...
0
votes
1answer
41 views

Training accuracy is ~97% but validation accuracy is stuck at ~40%

I am trying to classify images into 27 classes using a Conv2D network. The training accuracy rises through epochs as expected but the val_accuracy and val_loss values fluctuate severely and are not ...
0
votes
1answer
17 views

How to preprocess data for image classification from a .txt file?

Basically my issue is that im building an image classification model using AlexNet. I have this pre-split dataset thats already split into training, test, validation. However the issue is that these ...
0
votes
0answers
5 views

Comparision between SSIM and MAD Image Quality Assessment Algorithms

I have been working on Most Apparent Distortion(MAD) tool to evaluate the quality of images. I have read a paper that compares SSIM, PSNR, FSIM, etc. with MAD. I am uncertain about some calculations ...
0
votes
0answers
13 views

How to deal with images with textual noise?

I have a dataset of images collected from google and bing images (scraped). basically I want to classify these images into binary classes (positive, negative). Images that contain a text originally ...
0
votes
1answer
27 views

Cat Classifier becomes worse the more you train it

I am using a dataset from kaggle to train a feed forward neural-neteork with no convolutional layers. I wanted to try it this was as a learning exercise with Pytorch without Transfer Learning and ...
1
vote
2answers
56 views

Image Classification low accuracy

I have a dataset that has two folders for training and testing. I am trying to determine whether a patient has an eye disease or not. However, the images I have are hard to work with. I've ran this ...
0
votes
0answers
11 views

Loss function for non-uniform distribution in pixel regression?

Goal: Given RGB images (x,y,3) and a grayscale heatmap (x,y,1), predict the heatmap using the RGB image as input to a neural network implemented inside Keras. Approach: Multiply heatmap by (1./255) ...
0
votes
0answers
20 views

CNN RNN Video Classification Handle Different Frame Size

I'm working on a project which classify videos using CNN+RNN. I extract frames from each video and use these frames in order to classify each of them. The dataset contains videos which have different ...
0
votes
1answer
15 views

Image classification: Predict all objects' classes without bounding boxes

I'm trying to identify the problem here: I want to input an image and output the classes associated with all the objects in that image, not necessarily predict bounding boxes. I have been looking for ...
1
vote
0answers
15 views

what's the SOTA for medical imagery classification for diagnostic purposes?

Many medical image datasets - Ultrasound for example - have a time component that is quite powerful. But some of the papers I have read use ConvNets and seem to ignore temporality. Have there been ...
0
votes
0answers
11 views

Epoch 1/5 won't stop

When i run my code with 5 epochs, code gets stuck at first epoch and run continuesly. I tried applying various parameters but couldn't make it. here is my code... ...
0
votes
0answers
15 views

Softmax for binary classification in CNNs: dependent on pixel normalization?

I'm using a 2 input softmax layer as the final stage in a CNN for binary classification. Depending on how image input pixels are scaled, the inputs into this final layer can be too small to drive a ...
0
votes
1answer
22 views

Can I plug models like Linear Regression into a CNN feature map result?

I was learning about image recognition on the Orange Software and I saw that I can feed my image database into a CNN(they call image embedding) that has as output a feature map of the image and then I ...
0
votes
0answers
16 views

Debugging VGG16 Convergence Issues: Effect of Image Normalization and Weight Initialization

I've implemented VGG16 in Keras with 2 output classes for the Kaggle 'dogs v. cats' dataset as a learning exercise. I'm trying to understand the training behavior that I'm seeing. For all my tests, I ...
0
votes
1answer
16 views

Get Label Statistics of Image Dataset

I have a labeled image dataset, where the images are in subfolders and there is one Pascal XML per image with the labels. I would like to compute stats like: how many images have exactly two labels? ...
1
vote
0answers
25 views

class activation mapping when accuracy is 100%

I am a beginner to image classification and apologies beforehand if the question I am asking is dumb. I am currently using the following model: ...
1
vote
1answer
35 views

How to plot an image from a series of bits inPython?

I am given a dataset of 0s and 1s for some handwritten letters (below is a series for one image) and i'd like to visualize them in python. How can this be achieved? ...
1
vote
0answers
47 views

Gender Prediction from Offline Handwriting Using Convolutional Neural Networks

Starting from the fact that handwritten documents style are gender-dependent (male and female have different writing styles), I'm trying to predict writer's gender from its handwritten scripts using ...
0
votes
1answer
32 views

predict_classes() returning only 0 or 1 for multiclass image classification

I am trying to build a multi class image classifier but the only returns 0 or 1 . Why is it not returning "Rock" , "Paper" , "Scissor" ? and why only 0 and 1 but not 2? CODE: ...
1
vote
1answer
13 views

After performing data Augmentation on tf.data.Dataset, should i MERGE it with original tf.data.Dataset?

Kind of a silly question, but I read that data Augmentation can be used in order to solve problem of small datasets. In my case, I've got a dataset with 5 different classes and around 2k examples per ...
0
votes
1answer
13 views

I am not getting classification output by predict_generator()

I am trying to classify pre-downloaded images from my dataset to "Rock" , "Paper" , "Scissor" classifications but I am getting outputs as numbers. I have already divided the dataset to Train folder ...
0
votes
0answers
10 views

What is the difference between a convolutional neural network and reinforced learning in detecting MR anomalies?

I bumped into this paper on using deep learning to discover MRI lesions, using reinforcement learning to do so. I'm a novice in data science and thus far I've believed convolutional neural networks (...
1
vote
0answers
12 views

From Patch-based Classifier to Full Image classifier

I was wondering if it is feasible to train patch-based image classifier, due to small amount of data, and then use it in order to initialize training for full image classification, but this time on ...
1
vote
3answers
76 views

Classifying boat images

I trying to get some experience by exploring the following Kaggle dataset: https://www.kaggle.com/clorichel/boat-types-recognition/version/1 It consists of 1500 pictures of boats classified in 9 ...
1
vote
2answers
68 views

How to improve accuracy in the following code?

I have the about 43 different categories of traffic signs images data. If I am using the small data of 3 categories the maximum accuracy I am getting is around 65% and I have tried a lot of different ...

1
2 3 4 5
11