Searching for Face Recognition Using Gabor Features And Support Vector Machines information? Find all needed info by using official links provided below.
https://www.researchgate.net/publication/229042655_Gabor_Features_and_Support_Vector_Machine_for_Face_Identification
A novel Support Vector Machine (SVM) face recognition method using optimized Gabor features is presented in this paper. 200 Gabor features are first selected by a boosting algorithm, which are ...Author: Linlin Shen
https://dl.acm.org/citation.cfm?id=2079468
This paper presents a face recognition algorithm by using Gabor wavelet transform for facial features extraction and Support Vector Machines (SVM) for face recognition, Gabor wavelets coefficients are used to represent local facial features.Cited by: 4
https://www.sciencedirect.com/science/article/pii/S0045790612002534
This paper presents a novel and uniform framework for face recognition. This framework is based on a combination of Gabor wavelets, direct linear discriminant analysis (DLDA) and support vector machine (SVM). First, feature vectors are extracted from raw face images using Gabor wavelets.Cited by: 30
https://www.semanticscholar.org/paper/A-SVM-face-recognition-method-based-on-key-points-Qin-He/7be2de8ca6d03719539d9457928357fe0056d202
This paper presents a novel face recognition approach based on support vector machine and Gabor-featured key points, which takes technological advantages of both support vector machine and Gabor feature extraction. The main contributions of this paper therefore lie in the following aspects: (1) support vector machine is successfully applied to face recognition by using Gabor features of key ...
https://www.diva-portal.org/smash/get/diva2:239370/FULLTEXT01.pdf
Multiview Face Detection Using Gabor Filters and Support Vector Machine Bachelor’s Thesis in Computer Systems Engineering ... ABSTRACT Face detection is a preprocessing step for face recognition algorithms. It is the localization of face/faces in an image or image sequence. ... which is a Support Vector Machine (SVM) on a reduced feature ...
https://pdfs.semanticscholar.org/0190/caa35ab699f6f98dd7c75871f11d0d635644.pdf
Analysis and Support Vector Machine. Face recognition using Gabor filters was firstly introduced by Martin Lades et al. [18], and soon proved to be a very effective means in human facial features extraction. Xiao-ming [13] proposed a face recognition algorithm combined a vector features consisting of
https://ieeexplore.ieee.org/document/1527850/
Abstract: This paper presents a novel face recognition approach based on support vector machine and Gabor-featured key points, which takes technological advantages of both support vector machine and Gabor feature extraction. The main contributions of this paper therefore lie in the following aspects: (1) support vector machine is successfully applied to face recognition by using Gabor features ...
https://ieeexplore.ieee.org/document/1251793/
Abstract: Face recognition problem is challenging because face images can vary considerably in terms of facial expressions, lighting conditions and so on. This paper introduces a novel face recognition using support vector machines with the robust feature extracted by kernel principal component analysis (KPCA), which is robust to facial variations.
https://www.mathworks.com/matlabcentral/fileexchange/29834-face-detection-using-support-vector-machine-svm
Jan 06, 2011 · Face Detection using Gabor feature extraction and support vector machines (SVMs)Reviews: 17
https://link.springer.com/chapter/10.1007/11539117_20
Abstract. This paper presents a face recognition algorithm by using Gabor wavelet transform for facial features extraction and Support Vector Machines (SVM) for face recognition, Gabor wavelets coefficients are used to represent local facial features.Cited by: 4
How to find Face Recognition Using Gabor Features And Support Vector Machines information?
Follow the instuctions below:
- Choose an official link provided above.
- Click on it.
- Find company email address & contact them via email
- Find company phone & make a call.
- Find company address & visit their office.
