Face recognition: Past, present and future (a review)
Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …
behavioral characteristics of an individual. The main feature of biometric systems is the use …
A survey on deep learning based face recognition
Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …
increasing interests in face recognition recently, and a number of deep learning methods …
Plant species recognition methods using leaf image: Overview
Plant plays an important role in agricultural, industrial, medicine, environmental and
ecological protection. Recently, with global warming, biodiversity loss, rapid urban …
ecological protection. Recently, with global warming, biodiversity loss, rapid urban …
A survey of sparse representation: algorithms and applications
Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …
processing, image processing, computer vision, and pattern recognition. Sparse …
A full stage data augmentation method in deep convolutional neural network for natural image classification
Q Zheng, M Yang, X Tian, N Jiang… - Discrete Dynamics in …, 2020 - Wiley Online Library
Nowadays, deep learning has achieved remarkable results in many computer vision related
tasks, among which the support of big data is essential. In this paper, we propose a full stage …
tasks, among which the support of big data is essential. In this paper, we propose a full stage …
2D-human face recognition using SIFT and SURF descriptors of face's feature regions
Face recognition is the process of identifying people through facial images. It has become
vital for security and surveillance applications and required everywhere including …
vital for security and surveillance applications and required everywhere including …
Log-euclidean metric learning on symmetric positive definite manifold with application to image set classification
Abstract The manifold of Symmetric Positive Definite (SPD) matrices has been successfully
used for data representation in image set classification. By endowing the SPD manifold with …
used for data representation in image set classification. By endowing the SPD manifold with …
A novel key-frames selection framework for comprehensive video summarization
C Huang, H Wang - IEEE Transactions on Circuits and Systems …, 2019 - ieeexplore.ieee.org
Video summarization (VSUMM) has become a popular method in processing massive video
data. The key point of VSUMM is to select the key frames to represent the effective contents …
data. The key point of VSUMM is to select the key frames to represent the effective contents …
Multi-manifold deep metric learning for image set classification
In this paper, we propose a multi-manifold deep metric learning (MMDML) method for image
set classification, which aims to recognize an object of interest from a set of image instances …
set classification, which aims to recognize an object of interest from a set of image instances …
Pixel-wise regression using U-Net and its application on pansharpening
Convolutional neural networks are widely used for solving image recognition and other
classification problems in which the whole image is considered as a single object. In this …
classification problems in which the whole image is considered as a single object. In this …