is a system of grouping objects of study or observation in accordance with their common features. The classification problem is a formalized task in which a set of objects (cases), separated in some way to classes.

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12 views

Good color distance metric for classifying color pairs

I have some two tone origami paper. This particular paper comes in six types, each with a different pair of colors. Here's an image that shows all six: Given a picture of one of these sheets, I ...
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11 views

Outlier removal before or after Kalman filtering?

I am getting radar data points in form of (x,y) coordinate system relative to my position every ms.[around 10-15 data points]. Now, inorder to have better position estimate of the points, I would like ...
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1answer
38 views

Classifying animated GIFs as animation or film

Is there any known way of differentiating between frames of real footage and animated content? It seems like there's probably range of colors more likely to appear in a histogram for real footage, or ...
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16 views

Useful features for classifying color images

I have two sets of images. In one set, the background and foreground differs significantly in color (either background is dark and foreground is light or vice versa). What would be some useful ...
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1answer
13 views

Binary classification of grayscale image with little texture

I want to carry out a binary classification/segmentation on a grayscale image with very little texture. The only prior knowledge that's supposed to be available is that the object of interest is ...
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0answers
16 views

Fixed-length training data from variable-length signals for dictionary learning

My question relates to the topic of dictionary learning for 1-D signal classification. In a nutshell, I have a training dataset of N signals that belong to one of two classes, and I want to find a ...
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0answers
72 views

How to classify accelerometer data?

I am trying to detect if a car did accelerate or did brake by using the accelerometer of the iPhone. In the figure below I plotted the collected data. (To collect the data the phone was laying flat ...
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1answer
31 views

How to choose the number of codewords in bag of words model

In the bag of words model, generally is it better to have more codewords or less? For example, if I have 1000 x 20 raw features, then what would be good value for codebooks? I am thinking of smaller ...
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0answers
27 views

Comparing two signal outputs from two clients on a networked computer game to identify lag

Basically, I'm running a server and two clients of the Unreal Engine and trying to figure out if there is lag in player movement on one of the clients (the clients are different in way that's not ...
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1answer
254 views

Feature extraction for sound classification

I'm trying to extract features from a sound file and classify the sound as belonging to a particular category (eg : dog bark, vehicle engine e.t.c). I'd like some clarity on the following things : 1) ...
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1answer
56 views

Missing Data in Machine Learning Classification

I have a training set of 4000 for ML with 36 features, two-class classifier. -But consider that due to some discrepancy feature no. 25 is missing for half of the data. But during data ...
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0answers
23 views

OpenCV: Is NormalBayesClassifier::train function running ok?

I am have the code from here. I have changed the images with some of my own and I have seen that SVM is not working. That is not a problem because I have found on ...
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0answers
92 views

Using ICA on EEG signals for feature extraction

I am attempting to use ICA (FastICA via scikit-learn) on EEG signals from seven electrodes per subject for feature extraction and identity classification – that is to extract signal which is related ...
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0answers
40 views

Intelligent feature vector for an image classification problem

I am a person who loves to learn machine learning from an application point of view. My Objective : To learn machine learning by doing examples in MATLAB or Python like environments. The priority ...
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3answers
289 views

Best way to remove unwanted region from image

I am finding the techniques to remove unwanted regions (small dots) from image. I have an image that includes object and some unwanted region (small dots- see first image). I want to remove it. Hence, ...
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1answer
63 views

What Matlab Classifiers to use

I'm currently trying to decide what classifier to use for my snore detection algorithm. Which uses some features like Zero cross rating, frequency band energy, first formants... The classifiers which ...
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3answers
104 views

What does natural scene image data-set mean?

I came across a paper that is trying to classify and detect object(s) present in what they call a natural scene data-set. They have images containing objects like cars, bikes and people. Can anyone ...
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0answers
40 views

Frequency contour cross-correlation

I'm trying to segment (or extract) different calls from a spectrogram. My current method, calculates a threshold value (variance) and then using RMS can detect voiced/unvoiced signals: $$ Thres = (1 ...
1
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2answers
97 views

what is the output of BoW after an image has been trained with SIFT algorithm and k-means

SIFT algorithm provides a 128 dimensional feature vector that is used for image classification.When all the interest points(key points) are taken together and K-means clustering is applied,the image ...
2
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3answers
132 views

Detection of wobbling sound with rising notes

In an audio file I would like to find calls of a specific bird specie, one that makes wobbling sound with rising notes. Can you recommend what would be the best audio feature to calculate in time or ...
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1answer
42 views

What's a good classification algorithm for a large amount of classes?

My requirements are these: Fast classification of vectors of length 100 to one of 30000 classes Iterative learning (can improve the model after it was first learnt) Preferably available ...
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0answers
121 views

Using Bhattacharyya Distance for feature selection

I have a set of 240 features extracted using Image Processing. The objective is to classify test cases into 7 different classes after training. For each class there are about 60 observations(viz, I ...
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2answers
142 views

Guidance/Brainstorming for a mapping/classification problem

I'm quite new to machine learning/data mining and I'm struggling to find the correct path for my problem and would appreciate some guidance or criticism of my proposed solution i.e. is there a ...
0
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1answer
66 views

Music/Speech Classification: How are frame based features used in a feature vector?

I'm a little confused on how frame based high dimensional features such as mfcc's and bfcc's are applied in the classification of musical instruments. Are statistical measures of the features used ...
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3answers
124 views

What is the standard way to handle images of different sizes for classification?

I'd like to create an image classifier that takes a set of labeled images and creates a classifier to be used on some unknown images. Most of the examples I see assume all images are the same size (m ...
3
votes
2answers
696 views

Mahalanobis vs Normalization+Euclidean

I'm using a set of features extracted from a signal for classifying the data window with KNN algorithm. Since the features have different value ranges, their influence on distance calculation is ...
3
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3answers
167 views

Low recognition rates using GMM for image classification

I want to use GMM for image classification. So, I have extracted SIFT features from each image in the corpus. Then, I apply EM algorithm to learn GMM parameters (I have coded it in matlab). I get ...
6
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1answer
113 views

Vehicle segmentation and tracking

I've been working on a project for some time, to detect and track vehicles in video captured from UAV's, currently I am using an SVM trained on bag-of-feature representations of local features ...
1
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1answer
147 views

Object Classification using pyramid match kernel

I have been reading up on the pyramid match kernel as an alternative to using the bag-of-words model for object classification using a SVM. The bag-of-words model provides a model for transforming a ...
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0answers
121 views

Evaluation of Keypoint Detector and Feature Descriptor Combos for Vehicle Detection

I am currently doing a research project into the effectiveness of different keypoint detector and feature descriptor combinations for the task of vehicle detection. At the moment I am using a SVM for ...
2
votes
1answer
81 views

Classifying 2D shapes by the smoothness of their boundaries

I'm doing image analysis, and I want to classify smooth objects (has smooth boundaries) from non-smooth objects (has zigzag-like boundaries). Which feature should be fed into ML framework? What are ...
3
votes
1answer
138 views

Recognizing hand-written archaeological signs

I have 75 images of handwritten signs from which I extracted 7 Hu moments and solidity features. How can I find similarities among them to train a classifier and predict the value? I thought SVM was a ...
3
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0answers
106 views

Grouping clusters using Mahalanobis distances

I need to know the "number of clusters" in a dataaset. To find the number of clusters, I am using a Gaussian Mixture model fitting, bear with me, Because the underlying distributions (each cluster) ...
8
votes
1answer
4k views

Image classification using SIFT features and SVM

I am hoping someone can explain how to use the bag of words model to perform image classification using SIFT/SURF/ORB features and a support vector machine? At the moment I can compute the SIFT ...
8
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3answers
860 views

Why transforming the data to a high-dimensional feature space in which classes are linearly separable leads to overfitting?

I read in my book (statistical pattern classification by Webb and Wiley) in the section about SVMs and linearly non-separable data: In many real-world practical problems there will be no linear ...
4
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1answer
367 views

Support Vector Machine: A non-probabilistic binary linear classifier

I read that SVM is a supervised learning method, it is also a non-probabilistic binary linear classifier. I understand why it is binary because it classifies our training pattern to two classes $w_1$ ...
8
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3answers
3k views

Scale and Rotation invariant feature descriptors

Can you list some scale and rotational invariant feature descriptors for use in feature detection. The application is for the detection of cars and humans in video captured by a UAV, using a ...
3
votes
1answer
546 views

KNN method for different values of K on a handwritten digit data set

We're supposed to use KNN (K Nearest Neighbor) method for different values of K to classify a handwritten digit data set. The problem is, this is the first time I want to do a project like that in ...
2
votes
1answer
552 views

How to do people detection from bird eye view?

I'm trying to do people detection from bird eye view. Actually, it is not a normal bird eye view because I don't have RGB images but I have disparity map, depth map as well. In these kind of images, ...
8
votes
1answer
193 views

Recognizing data clustered into shapes

I am working on a project in Python to detect and classify some bird song, and I have found myself in a position where I need to convert a wave file into frequency vs. time data. This hasn't been too ...
7
votes
1answer
439 views

How can I automatically classify peaks of signals measured at different positions?

I have microphones measuring sound over time at many different positions in space. The sounds being recorded all originate from the same position in space but due to the different paths from the ...
10
votes
1answer
4k views

How do I retrieve texture using GLCM and classify using SVM Classifier?

I'm on a project of liver tumor segmentation and classification. I used Region Growing and FCM for liver and tumor segmentation respectively. Then, I used Gray Level Co-occurence matrix for texture ...
8
votes
2answers
364 views

Good metric for qualitatively comparing image patches

I am trying to "match" little square patches in an image. At first glance, it seems reasonable to simply do a Euclidean distance style comparison of two of these arrays to get a "similarity" measure. ...
7
votes
2answers
258 views

How can I distinguish between two similar EEG signals?

I have two EEG signals that are very similar. The difference is only in amplitudes. However, they are coming from two different cognitive processes. What are some methods, beside FFT, for ...
9
votes
2answers
306 views

What methodology to use for discrimination of different (musical?) tones

I am trying to research and figure out how best to attack this problem. It straddles music processing, image processing, and signal processing, and so there are a myriad number of ways to look at it. ...
11
votes
3answers
489 views

Texture Classification via DCT

How viable would it be to classify the texture of an image using features from a discrete cosine transform? Googling "texture classification dct" only finds a single academic paper on this topic, ...