Questions tagged [classification]

For questions related to the placement of individual cases into categories, such as is essential in fraud detection, spam detection, quality control, prediction of user or market responses, automated organizing or indexing, assigning objects in view to types of obstacles or risks, writing or typing recognition, phonic recognition, .

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38 views

Hand-Signs Recognition using Deep Learning Convolutional Neural Networks

I am developing a CNN model to recognize 24 hand-signs of American Sign Language. I have 2500 Images/hand-sign. The data split is: Training = 1250 Images/hand-sign Validation = 625 Images/hand-sign ...
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28 views

Finding the 'ultimate resolution' of an ANN

I want to use a neural network to predict the refractive index of a solution. My thinking is, instead of immediately training on many samples, I will first find the 'ultimate resolution' of the ...
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22 views

Which paper introduced the term “softmax”?

Nowadays, the softmax function is widely used in deep learning and, specifically, classification with neural networks. However, the origins of this term and function are almost never mentioned ...
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1answer
69 views

Can maximum likelihood be used as a classifier?

I am confused in understanding the maximum likelihood as a classifier. I know what is Bayesian network and I know that ML is used for estimating the parameters of models. Also, I read that there are ...
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1answer
52 views

How to use a deep learning network on new data-set?

I am trying to use a network for classification. This network works very well on the author's example data, but doesn't work on new data. Currently, I am using the popular EEG Motor Movement/Imagery ...
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1answer
70 views

Is it possible to classify resistors using ResNet50?

I want to train ResNet50 model using resistor images like below: I tried it by collecting data from google images and there were quite few. So accuracy was very low (around %10) but I wonder If it is ...
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1answer
56 views

Bayes error rate formula clarification

My questions concern a particular formulation of the Bayes error rate from Wikipedia, summarized below. For a multiclass classifier, the Bayes error rate may be calculated as follows: $$p = 1 - \...
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8 views

Why is 'scatter' used instead of variance in LDA?

I've been reading about Fisher's Linear Discriminant Analysis lately, and I noticed that the objective function (particularly for two-class classification) to be maximized contains scatter terms ...
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17 views

accessible subset of data impacts performance

I have a problem with a subset of my data which is as follows: I can train a model (doesn't matter what, xgboost, BERT, etc., it is a text classification problem), on my data and get a decent ...
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6k views

Binary classifier that minimizes false positive error

I have a binary classification problem, where a false positive error has a very big cost compared to the false negative error. Is there a way to design a classifier for such problems (preferably, ...
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16 views

Binary classification to recognize blobs on pictures generates many false-positive results

I am training a NN for blobs vs non-blobs recognition. Blobs example: Non-blobs: Keras architecture is: ...
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1answer
25 views

What is the advantage of having a stochastic classification procedure?

What is the advantage of having a stochastic/probabilistic classification procedure? The classifiers I have encountered so far are as follows. Suppose we have two outcomes $A = \{0,1\}$. Given a ...
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2answers
2k views

How successfully can convnets detect NSFW images?

For example, search engine companies want to classify their image searches into 2 categories (which they already do that) such as: NSFW (nudity, porn, brutality) and safe to view pictures. How can ...
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39 views

Why don't we use trigonometric functions for the output neurons?

Why don't we use a trigonometric function, such as $\tan(x)$, where $x$ is an element of the interval $[0,pi/2)$, instead of the sigmoid function for the output neurons (in the case of classification)?...
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1answer
31 views

How to use speaker's information as well as text for fine-tuning BERT?

I want to classify my corporate chat messages into a few categories such as question, answer, and report. I used a fine-tuned BERT model, and the result wasn't bad. Now, I started thinking about ways ...
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1answer
19 views

How to split data into training validation and test set when the number of data in classes varies greatly?

I have 5 classes of pictures to classify: 0 -> ~3 200 (~800 initial number before interference and duplication) 1 -> ~9 000 (I reduced from ~90 000) 2 -> ~8 000 3 -> ~3 000 4 -> ~7 200 How to ...
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2answers
119 views

How do I improve accuracy and know when to stop training?

I am training a modified VGG-16 to classify crowd density (empty, low, moderate, high). 2 dropout layers were added at the end on the network each one after one of the last 2 FC layers. network ...
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2answers
441 views

How to use BERT as a multi-purpose conversational AI?

I'm looking to make an NLP model that can achieve a dual purpose. One purpose is that it can hold interesting conversations (conversational AI), and another being that it can do intent classification ...
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0answers
20 views

How to train image segmentation task with only one class?

Is there a neural network that has architecture optimizations for segmenting only one class (object and background)? I have tried U-net but it is not providing good enough results. I am wondering if ...
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12 views

Input with variable length Classification problem

I have a dataset with patient information with discrete labels (labels are stages of a particular disease) which needs to be predicted (Basically a classification problem). The data set looks ...
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1answer
40 views

Can training a model on a dataset composed by real images and drawings hurt the training process of a real-world application model?

I'm training a multi-label classifier that's supposed to be tested on underwater images. I'm wondering if feeding the model drawings of a certain class plus real images can affect the results badly. ...
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36 views

Is subsection generation $O(n^4)$

When I say template matching, I'm referring to finding occurrences of a small image (the template) in a larger image. The OpenCV library provides the trivial solution, that slides the template over ...
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1answer
82 views

Should I use single or double view for gender recognition?

My project requires gender recognition of people shown on the given images, with more than one person per image. However, these people can be positioned in frontal or side view(passing by ...
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0answers
19 views

How can I predict the label given a partial feature vector?

Most of the traditional machine learning algorithms need a feature vector of a constant dimension to predict the label. Which algorithms can be used to predict a class label with a shorter or ...
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1answer
57 views

How difficult is this sound classification?

I want a microphone to pick up sounds around me (let's say beyond a 3 foot radius), but ignore sounds made at my desk, such as the rustling of paper, clicking a mouse and typing, my hands brushing up ...
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1answer
32 views

Is it a good idea to overfit on a small part of your data for faster model convergence?

I working on a classification problem that needs to detect patterns on a time serie. Basically, there's a catch-all class that means "no pattern detected", the other are for the specific patterns. The ...
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2answers
156 views

Can machine learning algorithms be used to differentiate between small differences in details between images?

I was wondering if machine learning algorithms (CNNs?) can be used/trained to differentiate between small differences in details between images (such as slight differences in shades of red or other ...
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1answer
25 views

What is the meaning of “easy negatives” in the context of machine learning?

What does the term "easy negatives" exactly mean in the context of machine learning for a classification problem or any problem in general? From a quick google search, I think it means just negative ...
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0answers
152 views

Is it possible to learn to estimate the minimum value in a table?

Is it possible to classify or learn to estimate the minimum value in a table if the values are integer and represented 32 bits (and we can input all variables at the same moment, like in system on a ...
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1answer
40 views

Recognising Noise in Simple Classification

I have created a classifier for some simple gestures using an input layer, a hidden layer with tanh activation and an output softmax layer. I'm also using the Adam optimiser. The network classifies ...
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0answers
20 views

Incorporating domain knowledge into recurrent network

I am currently trying to solve a classification task with a recurrent artificial neural network (RNN). Situation There are up to 350 inputs (X) mapped on one categorical output (y)(13 differnt ...
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0answers
21 views

Is there a classification task with multiple attribute regression?

I'm trying to look for a task that predicts a discrete label first (classification), and then predicts the multiple continuous attributes of the predicted class. I found some papers about multi-output ...
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1answer
54 views

How to classify human actions?

I'm quite new to machine learning (I followed the Coursera course of Andrew Ng and now starting deeplearning.ai courses). I want to classify human actions real-time like: Left-arm bended Arm above ...
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1answer
420 views

Indian Traffic Sign Dataset [closed]

I am looking for the Indian Dataset of traffic signs. There is a dataset developed recently IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments which contains ...
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1answer
213 views

Is a dataset of roughly 700 sentences of an average length of 15 words enough for text classification?

I'm building a customer assistant chatbot in Python. So, I am modelling this problem as a text classification task. I have available more or less 7 hundred sentences of an average length of 15 words (...
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2answers
45 views

Difference between training accuracy and calculating accuracy with class prediction

I have trained my neural network with a dataset of 11200 images, and its validation accuracy was 96%. I saved my model and load its weights to the same neural network. I chose 738 images of my dataset ...
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0answers
18 views

How does sampling works in case of imbalanced image datasets?

I am solving a problem of image classification of the image dataset for 3 classes. Dataset is highly imbalanced. How will sampling (either over- or under-sampling) work in that case? Should I remove (...
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0answers
10 views

How can I efficiently detect subsections?

I have a feeling this question has a lot of research into it, but I can't find any relevant results. I'm trying to compare the similarity of audio Here, I have 2 virtually identical samples; however,...
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1answer
47 views

An infinite VC dimensional space vs using hierarchical subspaces of finite but growing VC dimensions

I have the following scenario. I have a binary classification problem, whose underlying function is a step function. The probability distribution of feature vectors is a uniform over the domain. Case ...
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2answers
42 views

Using AI to enhance customer service

I'm trying to find out how AI can help with efficient customer service, in fact call routing to the right agent. My usecase is given context of a query from a customer and agents' expertise, how can ...
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1answer
196 views

Detecting playing cards with a neural network

I want to train an AI to detect playing cards. For that reason I bought many different decks, scanned and labeled them. Next up would be to create training data with an augmentation library. I found ...
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1answer
18 views

How are weights for weighted x-entropy loss on imbalanced data calculated?

I am trying to build a classifier which should be trained with the cross entropy loss. The training data is highly class-imbalanced. To tackle this, I've gone through the advice of the tensorflow docs ...
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1answer
44 views

How to draw bounding boxes for gender classification?

I wonder what is the better way of drawing rectangles on images for gender classification. My task is to create a classifier (CNN based) to detect gender from pictures of entire bodies (not just faces)...
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1answer
791 views

Loss functions for Hierarchical Multi-label classification?

I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels like multilayer perceptron ( MLP )branch ...
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1answer
55 views

Relationship between input range and channel means, standard deviations for CNNs

So, I'm using a pretrained pnasnet5large model to do some image classification (https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/pnasnet.py) In the file, it ...
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0answers
17 views

Is the high dimensionality of input vectors a problem for a radial basis function neural network?

I have a dataset A of videos. I've extracted the feature vector of each video (with a convolutional neural network, via transfer learning) creating a dataset B. Now, every vector of the dataset B has ...
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18 views

Are there any general guidelines for dealing with imbalanced data through upsampling or downsampling?

Are there any general guidelines for dealing with imbalanced data through upsampling/downsampling? This Google developer guide suggests performing downsampling with upweighting, but for the most ...
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2answers
59 views

Combine two feature vectors for a correct input of a neural network

Let's consider this scenario. I have two conceptually different video datasets, for example a dataset A composed of videos about cats and a dataset B composed of videos about houses. Now, I'm able to ...
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6 views

Would truncating a trained CNN help with generalisation?

Say I have a very small dataset to do transfer learning with, for image classification purposes. And say that I know that what's most important in classifying these images is low level details like ...
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2answers
76 views

Two data classes for a convolutional neural network, can one have a LOT more images for training than the other?

I have two classes in the training set: one that has images with a feature and the other of images without that feature. Can there be a LOT more images with "no feature" so I can fit in all possible ...

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