Fig 1 - uploaded by Nova Hadi Lestriandoko
Content may be subject to copyright.
Source publication
This paper presents an analysis of the recognition performance of LBP at different frequency bands to exploit their discriminative information. The work presented in this paper is part of an investigation about which aspects of a face contribute to automated face recognition. Multi-resolution analysis, by means of wavelet transform, is commonly use...
Similar publications
The purpose of this paper is to present a straightforward framework for Heart Rate (HR) estimation from a Phonocardiogram (PCG) records and study the impact of murmur severity on HR. The system focuses primarily on data processing procedure, which is based on signal preprocessing using Maximal Overlap Discrete Wavelet Transform (MODWT) to delineate...
Strong pulse-like ground motions excited by a causative fault with a rupture propagation close to the shear wave velocity can induce significant earthquake hazards. The single original and horizontal rotation components of pulse-like ground motion were mainly considered in the last years, especially the generation mechanism of velocity pulse and it...
![Figure 2. EEG recording [4].](profile/Khalid-Hosny/publication/369498960/figure/fig2/AS:11431281130757099@1679926664491/EEG-recording-4_Q320.jpg)
Background:
Bio-signals are the essential data that smart healthcare systems require for diagnosing and treating common diseases. However, the amount of these signals that need to be processed and analyzed by healthcare systems is huge. Dealing with such a vast amount of data presents difficulties, such as the need for high storage and transmissio...
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
In this article, a novel NN structure that combines factorization machines, wavelet transform, and the RNN structure is proposed to improve the accuracy of ship motion prediction. In...
Context. Magnetic arcades in the solar atmosphere, or coronal loops, are common structures known to host magnetohydrodynamic (MHD) waves and oscillations. Of particular interest are the observed properties of transverse loop oscillations, such as their frequency and mode of oscillation, which have received significant attention in recent years beca...
Citations
... They also concluded that the region around the nose plays an important role in face detection. Lestriandoko et al. (2019) analyzed the different frequency band contributions to recognition using DWT and LBP. They also presented a block-based area contribution. ...
... Furthermore, Ahonen et al. (2004), Caifeng et al. (2005), Nikisins andGreitans (2012), andLoderer et al. (2015) analyzed the importance of the area (blocked-based area) of the face for recognition or detection using LBP. In detail, Lestriandoko et al. (2019) also compared the discriminative area of LBP between the clear dataset and the dataset containing face expression. They found that the dataset with face expression variation produced a smaller area of the discriminative component, especially on the face component shape. ...
The development of face recognition improvements still lacks knowledge on what parts of the face are important. In this article, the authors present face parts analysis to obtain important recognition information in a certain area of the face, more than just the eye or eyebrow, from the black box perspective. In addition, the authors propose a more advanced way to select parts without introducing artifacts using the average face and morphing. Furthermore, multiple face recognition systems are used to analyze the face component contribution. Finally, the results show that the four deep face recognition systems produce a different behavior for each experiment. However, the eyebrows are still the most important part of deep face recognition systems. In addition, the face texture played an important role deeper than the face shape.
We investigate the importance of the information contained in the area of the eyebrows for deep face recognition. An isotropic 2D Gaussian low-pass filter of varying bandwidth is used to remove discriminative information in the probe and reference images gradually. We measure the recognition performance of two deep learning-based face recognition systems as a function of the bandwidth of the low-pass filter applied to the eyebrows. Methods are tested on the frontal face and high-resolution images from the PUT database. The results showed that even though the eyebrows are important for recognition, deep learning still works well on facial images with removed eyebrows. Furthermore, we found that the discriminative information provided by eyebrows comes from their shapes, not their textures.
