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
votes
0answers
8 views

Choose proper(best) input size for CNN model?

I have different size images in my dataset for training. How we would choose proper(best) input size for a model? What I do is choosing average width and height of all images. Is there better of ...
-3
votes
0answers
35 views

What is the state of the art in deep learning for image feature representation? [closed]

I am relatively new to deep learning and want to build a model that extracts features from images which i can then use for classification or anomaly detection. I have searched for quite a while now, ...
0
votes
1answer
23 views

Creating a image classification model

I am working on a dataset to classify facial expressions. Dataset has 7 classes, training images 28000 and test images 7000. I created 2 models Model1: this model has 11 layers. Initially model was ...
0
votes
1answer
23 views

Machine learning algorithms for Geometrical objects shapes identification

Are there Machine learning algorithms which will take input dataset of all geometrical objects shapes as images in gif,jpg,tiff formats & output the geometrical shapes names? i.e. Geometrical ...
0
votes
0answers
21 views

ValueError: Shapes (None, 1) and (None, 11) are incompatible when training my Sequential model [closed]

The shape of images is print("Shape of Images:",Images.shape) print("Shape of Labels:",Labels.shape) While the model is ...
0
votes
2answers
36 views

Machine learning algorithms for interpreting Companies brand/s logo/s

https://www.google.com/search?q=Company+brand+logos&client=ms-android-lava&prmd=isnv&sxsrf=ALeKk0218I-1fMd-hNXX_fAF8_fu6EOotA:1600348128111&source=lnms&tbm=isch&sa=X&ved=...
0
votes
1answer
48 views

How to build a database of image data for machine learning?

I want to build a database of image data for machine learning. But how should this be done? I'm assuming people don't just dump all of their image data into a folder? Do they use a relational database ...
0
votes
0answers
7 views

Preparing training data for crop species classification from drone images

I have high resolution multispectral (R,G,B,NIR,RE bands) images of a field taken from MicaSense RedEdge mounted on a drone. There are various species of crops planted. I want to classify the crops or ...
1
vote
0answers
13 views

Does adding a class to a model increase its performance?

I am experimenting with object detection in images via CNN, to be more specific with yolov5 and faster RCNN. The models I use were pre-trained on the coco dataset before I finetune them. My dataset is ...
2
votes
1answer
38 views

Machine learning algorithms and Computer Vision technologies for detecting 52 playing cards deck

https://en.wikipedia.org/wiki/Standard_52-card_deck https://en.wikipedia.org/wiki/Playing_card https://www.google.com/search?q=playing+cards&client=ms-android-lava&prmd=sinv&sxsrf=...
0
votes
2answers
31 views

CNN: How do I handle Blurred images in the dataset?

I have 30% blurred images in each classes. I have a total of 10 classes. I'm not allowed to drop these blurred images. How do I train the model to get better accuracy for both blurred and nonblurred ...
1
vote
2answers
67 views

How to predict multiple images from folder in python

Here is the code for the Prediction of multiple images from the folder. But getting the same label(class) for all the images.I'm not able to find out why every image shows the same label. ...
0
votes
0answers
20 views

What are the best models developed for image classification

For inventory detection problem, when you cut single product images from the shelf, the next step you have to do is that you should label the product and identify which category this product belongs ...
0
votes
1answer
43 views

End-to-end ML project walkthrough [closed]

I am new to machine learning and have finished Andrew Ng's course on Coursera. I have just begun to tackle my first "real" ML problem - which is a binary classification problem. I was ...
0
votes
0answers
16 views

Which features can help to differentiate two similar images in deep learning?

I have used the Inception V3 model. There were 11 classes in training out of 5 classes that are (Visually look) Similar and that 5 classes were misclassified with other classes when testing the images....
0
votes
1answer
29 views

How to increase model's test accuracy?

I am using the InceptionV3 model for training. Here is the link for the code (https://github.com/maxmelnick/tensorflow/blob/no_random/tensorflow/examples/image_retraining/retrain.py) Initially I have ...
0
votes
1answer
34 views

How can I find if it is an overfitting problem?

I am new in Machine learning, and I want to detect emotions from the face. Preprocessing: I used equalizeHist to equalizes the histogram of grayscale images (JAFFE database with 213 images), in the ...
0
votes
2answers
21 views

how do the number of classes in an object detection model affect accuracy?

If I have, say, a Yolo or RetinaNet Object Detection Model... if I train it with 10 vs 50 classes, (assuming 3000 training data images per class), will the model with 10 classes perform similarly to ...
1
vote
1answer
55 views

How to increase model's prediction accuracy

I am using the InceptionV3 model for training. Here is the link for the code (https://github.com/maxmelnick/tensorflow/blob/no_random/tensorflow/examples/image_retraining/retrain.py) Initially I have ...
0
votes
1answer
17 views

[under/over]-sampling teaches model the wrong distribution?

TLDR: Will under/oversampling during the training phase teach the model the wrong distribution and adversely affect accuracy? Let us assume you want to train a classifier to differentiate between ...
0
votes
0answers
26 views

Can autoencoder latent variables to be used as features for classification?

I did some experiments on convolutional autoencoder by increasing the size of latent variables from 64 to 128. I used 4 covolutional layers for the encoder and 4 transposed convolutional layers as the ...
0
votes
2answers
36 views

Image multi class classifier CNN

I have a problem, im designing a multiclass classifier to classify medic images, I have to classify in which grade of desease is it, this are 6 grades , each time the joint deforms a little, so, mi ...
0
votes
0answers
23 views

How to recognize plaid / tartan?

I have an idea for a side-project: I'd like to be able to start with an image of a Scottish kilt, and automatically determine what tartan is used. For example, this is my (MacGill) tartan. Ideally, I'...
0
votes
1answer
16 views

Tagged dataset with photos for race detection

Looking for the tagged dataset, because I would like to identify race by photo. I tried using the UTKFace dataset from Kaggle, but it outputs hispanic and Arab people on images as ...
0
votes
1answer
36 views

Creating an “unclassified” class in Random Forest

I am trying to classify satellite based images by creating a region of interest and then classifying according to it. I am using a Jupyter notebook using python to do that. I used a Random forest ...
0
votes
0answers
11 views

Getting error while performing late fusion of audio and video feature vectors. Please help me resolve this

I am trying to build Multimodal emotion classifier for which I have created CNN based Audio and Video models separately. Below are the implemented CNNs: ...
0
votes
0answers
10 views

CNN not learning - Tensorflow implementation of a binary image classification problem

I designed a custom net architecture (16 layers net) for a binary image classification task and here some highlights: input image: 100x100x3 of two classes(car and person)(normalized and randomized) ...
0
votes
0answers
9 views

Generalise a CNN model for Question vs Spam . Techniques to generalise the model apart from more data

For my problem, every image which is not a picture of a question on a paper (either from text book or handwritten), is a spam. It means that each and every image in this world is a spam for my case ...
0
votes
0answers
10 views

Image classification tool for detection of small features

I have a dataset of images of damaged cars. Each image has an associated mask of overall damage and severity index of each type of damage. Unet successfully predicts the overall mask of damaged area ...
0
votes
0answers
31 views

Dot product as template matching with a linear classifier(cs231n)

I'm not sure I understand something from this article: https://cs231n.github.io/linear-classify/ In the context of linear classification of images, it is written: Interpretation of linear classifiers ...
0
votes
0answers
14 views

Where to save image features to avoid repeating extraction?

I am implementing Bag-of-Visual-Words. Part of that is SIFT, it has a task of extracting features and outputs a vector. Afterwards, the vector are clustered and made into a histogram. Histograms are ...
0
votes
0answers
12 views

Training images for gender and and age detection from face

Can someone please tell me if it is feasible to train my own set of facial images to detect gender and age without using any cloud architecture or paying some amount of money ? And , on an average how ...
0
votes
1answer
26 views

Suitable neural network type to classify text in images

I have images that contain text and I am not sure what is the type of NN that can do the job for me. Basically, it will have to read the images and understand the text in order to be able to classify ...
0
votes
0answers
8 views

Keras Predictions as a list of file names for each class

I've created a model using Keras, I have trained it with a training and validation set, and have used a test set filled with random number of images for each class. My test set consists of one folder ...
0
votes
1answer
35 views

Single image feature reduction at inference time : SVM

I am trying to train a SVM classifier using scikit-learn.. At training time I want to reduce the feature vector dimension. I have used PCA to reduce the dimension. ...
1
vote
0answers
37 views

Positive/negative training sample imbalance in multi-label image classifiers

I'm trying to train VGG-16 on the Pascal VOC 2012 dataset, which has images with 20 labels (and a given image can have multiple classes present). The examples are highly imbalanced, so I've "...
0
votes
0answers
14 views

How does one decide on the right image quality filters for a training and testing set?

What image quality metrics do people use to choose appropriate quality (e.g. focus, orientation, obstruction, etc.) images for important for image classification models? I would imagine anything that ...
2
votes
1answer
23 views

Difference between convolution structures

I am having a hard time understanding the difference what is a multichannel CNN: In the paper titled, "A Multichannel 2D Convolutional Neural Network Model for Task-Evoked fMRI Data ...
2
votes
1answer
150 views

Training CNN on a huge data set

I am trying to train an AlexNet image model on the RVL-CDIP Dataset. The dataset consists of 320,000 training images, 40,000 validation images, and 40,000 test images. Since the dataset is huge I ...
2
votes
0answers
46 views
1
vote
1answer
50 views

Understanding 'scale_boxes' in YOLO Algorithm of CNN

I'm studying Andrew NG's Convolutional Neural Networks and am in Week 3 of the course which deals with object detection using YOLO algorithm . I don't understand one section in the programming ...
1
vote
1answer
22 views

How do reshape an image to fit my Mnist Convolutional model?

I have done research but cannot seem to find what's wrong here I have created this model for Mnist digit clasification : ...
1
vote
2answers
39 views

How does SVM classify images?

I have read about SVM and understood that for complex divisions, the SVM theoretically plots the data into a higher dimensional plane such that the in the new dimension the data is linearly separable ...
2
votes
1answer
61 views

Training set of a NN that classify Cat or Not Cat

Is it possible to build a Convolutional Neural Network (using Keras, Tensorflow) that can give output as 1 for an image of a Cat and 0 for everything else? How would the training set look like? I mean,...
1
vote
1answer
13 views

Retraining of object detection models

I came across the concept of retraining of models a few days back. So tensorflow recommends to retrain an already trained model instead of making a new one from scratch so that the whole process takes ...
0
votes
0answers
17 views

Classifying Live Images From Camera Feed with bunch of objects in Background?

I can successfully run image classification if I feed examples from Google image to mobilenet model on Raspberry pi with Google Coral Edge TPU. However, if I feed live images from camera in my living ...
2
votes
0answers
20 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
14 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 ...
0
votes
1answer
21 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
2 3 4 5
12