Multiple Network Fusion with Low-Rank Representation for Image-Based Age Estimation

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Deep Unsupervised Domain Adaptation for Image Classification via Low Rank Representation Learning

Domain adaptation is a powerful technique given a wide amount of labeled data from similar attributes in different domains. In real-world applications, there is a huge number of data but almost more of them are unlabeled. It is effective in image classification where it is expensive and time-consuming to obtain adequate label data. We propose a novel method named DALRRL, which consists of deep ...

متن کامل

Feature Vector Fusion for Image Based Human Age Estimation

Abstract—Human faces, as important visual signals, express a significant amount of nonverbal info for usage in human-to-human communication. Age, specifically, is more significant among these properties. Human age estimation using facial image analysis as an automated method which has numerous potential real‐world applications. In this paper, an automated age estimation framework is presented. ...

متن کامل

Image Denoising Using Low Rank Minimization With Modified Noise Estimation

Recently, the application of low rank minimization to image denoising has shown remarkable denoising results which are equivalent or better than those of the existing state-of-the-art algorithms. However, due to iterative nature of low rank optimization, estimation of residual noise is an essential requirement after each iteration. Currently, this noise is estimated by using the filtered noise ...

متن کامل

Low-rank Representation for Enhanced Deep Neural Network Acoustic Models

Automatic speech recognition (ASR) is a fascinating area of research towards realizing humanmachine interactions. After more than 30 years of exploitation of Gaussian Mixture Models (GMMs), state-of-the-art systems currently rely on Deep Neural Network (DNN) to estimate class-conditional posterior probabilities. The posterior probabilities are used for acoustic modeling in hidden Markov models ...

متن کامل

Dimensionality Reduction Based on Low Rank Representation

Dimensionality Reduction is a common way to solve the problem of ‘curse of dimensions’, especially for image processing. Among all these methods, the linear methods are believed to have better performance in actual databases. This paper proposes a novel unsupervised linear dimensionality reduction method that based on low rank representation which aims at finding the subspace structure of the o...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Applied Sciences

سال: 2018

ISSN: 2076-3417

DOI: 10.3390/app8091601