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local feature

Enhancing Local Feature Extraction with Global Representation for Neural Text Classification

Enhancing Local Feature Extraction with Global Representation for Neural Text Classification

... Strong local feature driven models CNN (Kim, 2014) and DRNN (Wang, 2018) are chosen as base model and directly compared with our architecture in last two ...

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A Survey on Local Feature Based Face Recognition Methods

A Survey on Local Feature Based Face Recognition Methods

... recognition. But it is still challenging to differentiate the people with similar appearance and to recognize the same person who has different appearance due to different facial expression, pose, occlusion, illumination ...

7

Feature extraction: Face detection techniques and 3D object recognition based on local feature extraction

Feature extraction: Face detection techniques and 3D object recognition based on local feature extraction

... on local feature, the system needs to carry out three main phases: 3D keypoint detection, local surface feature description and surface ...A local surface is defined by the keypoint’s ...

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Learning Local Feature Descriptors for Multiple Object Tracking

Learning Local Feature Descriptors for Multiple Object Tracking

... The two approaches to embedding learning, which are relevant to our study, are the following: person re-identification (Re-ID) and learned local feature descrip- tors. While being similar in some aspects, ...

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Local feature analysis using higher-order Riesz transforms

Local feature analysis using higher-order Riesz transforms

... One of the advantages of the sinusoidal model is that it gives a phase-invariant estimate of the main linear symmetry of the local image structure. For example, the sinusoidal model orientation estimated using a ...

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Hybrid Invariant Local Feature Extraction For Medical Image Registration

Hybrid Invariant Local Feature Extraction For Medical Image Registration

... The following section summarizes the SURF algorithm, it is a robust local feature descriptor that is widely utilized in computer vision applications. This algorithm contains three major steps such as ...

6

Object based Image Retrieval using Local Feature Extraction and Relevance Feedback

Object based Image Retrieval using Local Feature Extraction and Relevance Feedback

... The first step of the proposed approach consists in to describe the visual attributes of the image samples for comparison and retrieval purposes. In this work, the image description is preliminary performed by using ...

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Exploiting Local Feature Patterns for Unsupervised Domain Adaptation

Exploiting Local Feature Patterns for Unsupervised Domain Adaptation

... to feature ag- gregation methods, such as vectors of locally aggregated de- scriptors (VLAD) (J´egou et ...generic local feature patterns and facilitate local feature alignment for ...

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Supervised Fuzzy Mixture of Local Feature Models

Supervised Fuzzy Mixture of Local Feature Models

... characterize local features, especially in a complex sys- tem, we propose a mixture of local feature models to overcome these ...developed feature-based model combination method is applied to ...

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Spam Filtering using K mean Clustering with Local Feature Selection Classifier

Spam Filtering using K mean Clustering with Local Feature Selection Classifier

... using Local feature classification methods with K mean clustering algorithm in classifier, for spam filtering term selection we are using Document frequency method, for feature extraction we are ...

5

Stable Local feature based Age Invariant Face
Recognition

Stable Local feature based Age Invariant Face Recognition

... sampled local feature description scheme, in which scale invariant feature transform (SIFT) and multi-scale local binary patterns (MLBP) serve as the local ...of local ...

6

3D FACE RECOGNITION USING LOCAL FEATURE BASED METHODS

3D FACE RECOGNITION USING LOCAL FEATURE BASED METHODS

... stable feature vector under facial expression, expression-insensitive signatures are constructed using weighted ...Each feature vector is normalized into [−1, +1] and quantized into a histogram with m ...

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A DCT-based Local Feature Extraction Algorithm For Palm-print Recognition

A DCT-based Local Feature Extraction Algorithm For Palm-print Recognition

... a feature vector with a very large ...the feature dimension, we propose to utilize the magnitudes corresponding to the dominant DCT coefficients as spectral ...desired feature, which also offers an ...

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Feature Cut: Video Object Segmentation Through Local Feature Correspondences

Feature Cut: Video Object Segmentation Through Local Feature Correspondences

... exploiting feature-based object detection research to propagate user- supplied segmentation information through video over long sequences, an example is shown in Figure ...

8

Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework

Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework

... a local facial feature based framework for both still image and video-based face ...on feature: feature averaging (Avg-Feature), Mutual Subspace Method (MSM), Manifold to Manifold ...

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Static Signature Verification Using Local Feature Extraction Based DRT And HMM

Static Signature Verification Using Local Feature Extraction Based DRT And HMM

... more useful in salt pepper noise cases. LBP (Local Binary Pattern) is efficient when there are a group of signatures to be tested which are signed using the same pen and has less presence of noise. If the ...

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COLOR TEXTURE CLASSIFICATION USING LOCAL &  GLOBAL METHOD FEATURE EXTRACTION

COLOR TEXTURE CLASSIFICATION USING LOCAL & GLOBAL METHOD FEATURE EXTRACTION

... and local feature set. Four feature sets are ...new feature set that has been used for color texture image ...this feature a global map is generated which represents measured intensity ...

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Nested Graph Representation for Visual SLAM based on Local and Global Feature Processing

Nested Graph Representation for Visual SLAM based on Local and Global Feature Processing

... visual feature can be captured from different angles or ...for feature detection and extraction, SIFT has proven to have the ability to find and match features with higher degree of uniqueness and ...for ...

8

Non-Linear Feature Extraction by Linear Principal Component Analysis Using Local Kernel

Non-Linear Feature Extraction by Linear Principal Component Analysis Using Local Kernel

... first feature extraction step in various researches and ...of local features) Hotta (2008b) was effective for object categorization but the computational cost is ...a local feature to all ...

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Application of Local Supervised Feature Selection Approach to Target Detection in Hyperspectral Imagery

Application of Local Supervised Feature Selection Approach to Target Detection in Hyperspectral Imagery

... autocorrelation-based feature selection (AFS), is proposed based on the TD ...reduced-dimensionality feature spaces is ...adding local spatial information to TD, dramatically improves the TD ...

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