feature vector

In machine learning, the data is often represented as a vector, sometimes called a feature vector.

Each point is used to generate a feature vector that describes the local image region sampled relative to its scale-space coordinate frame.

Then the every frequency amplitude of auditory correlogram was coded as a feature vector expressing present frequency band characteristic.

The distance function is used for similarity measure of image feature vector and realizes the matching of feature vector.

This paper presents a calculation of both beneficial and can effectively express the Grayscale color image feature vector.

Secondly, we sorted the feature vector by dictionary, and located the tampered region by utilizing the displacement vectors of image blocks.

Firstly, the steps of constructing scale space, detecting extrema and confirming key-points are employed to create SIFT feature vector.

For rotating machinery's vibration signal, we extract the traditional spectrum features, and obtain the feature vector.

After the feature vector is available, support vector machine(SVM) is used for classification.

The algorithm firstly expresses the text as feature word set and the technology extracting feature vector by statistical method.

Then, operate the feature extraction imagery and the feature vector map to detect the change information and determine their types.

Then, set the elements of each feature vector of SVM according to features of text layout, words and contents, etc.

This method combines some features of face and ears, then forms the higher-dimension feature vector.

A 31-dimension feature vector is selected which can best resemble the digit "s characteristic of construction and statistics. "

It is critical for fault diagnosis to extract the feature vector of fault signal effectively and to find the sensitive factors.

In view of the luminance and the chrominance of the image, the class feature vector is extracted.

A feature vector is assigned to a cluster which has the highest membership degree.

In dipeptide based prediction experiments of enzyme thermostability, the accurary when polar of amino acid was feature vector was 71. 9%.

Will be extracted after the six feature vector for normalized.

Based on RGB color space, this text gives the method of feature extraction and the method of compute the feature vector.

Before constructing fuzzy feature vector, we should first construct a fuzzy feature item set.

We can conclude that when the same feature vector is used, the performance of different machine learning algorithms gets little difference.

It is significant to study feature vector. This thesis focuses on feature extraction and feature selection.

Representation for Assembly Constraints with Mating Feature Vector Transformation

and the processing of the keyword power and semantic attribute for feature vector representation was added;

describes URL by feature vector, and calculates the distance with the key words set to classify URL;

The Classification of Time Series Employing Feature Vector and Binary Tree

Feature space, feature vector and feature extractor

Analysis of the oil pipeline leakage feature vector extraction based on wavelet packet

Feature Vector-Based Nude Picture Detection

An Image Segmentation Method Based on Velocity Feature Vector for Moving Target Extraction

Distributed clustering algorithm based on feature vector

A Extract and Measure Method of Image Multi-Feature Vector on CBIR

Underwater target recognition based on fractal feature vector

The Checking Method of Terrain Feature Vector Data