3D Patch-Based Sparse Learning for Style Feature Extraction

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود 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

Feature Extraction and Fusion Techniques for Patch-Based Face Recognition

Face recognition is one of the most addressed pattern recognition problems in recent studies due to its importance in security applications and human computer interfaces. After decades of research in the face recognition problem, feasible technologies are becoming available. However, there is still room for improvement for challenging cases. As such, face recognition problem still attracts rese...

متن کامل

Learning a Sparse Database for Patch-Based Medical Image Segmentation

We introduce a functional for the learning of an optimal database for patch-based image segmentation with application to coronary lumen segmentation from coronary computed tomography angiography (CCTA) data. The proposed functional consists of fidelity, sparseness and robustness to small-variations terms and their associated weights. Existing work address database optimization by prototype sele...

متن کامل

LBP-based Hierarchical Sparse Patch Learning for Face Recognition

Local Binary Pattern (LBP) features and its variants are computed on the patches with the fixed positions and a fixed size in images, while the limited variety of the size and position cannot accurately measure the nature of face image. In this paper, we propose a new learning method, Hierarchical Sparse Patch Learning (HSPL), to select face patches with different positions and sizes for face r...

متن کامل

Soft Multiple Winners for Sparse Feature Extraction

A simple and computationally inexpensive neural network method for generating sparse representations is presented. The network has a single layer of linear neurons and, on top of it, a mechanism, which assigns a winning strength for each neuron. Both input and output are real valued in contrast to many earlier methods, where either input or output must have been binary valued. Also, the sum of ...

متن کامل

Contextual Patch Feature Learning for Face Recognition

Local features, such as local binary patterns (LBP), have shown better performance than global feature in the problem of face recognition. However, the methods to extract the local features are usually given as fixed, and also neglect the class labels of the training samples. In this paper, we propose a novel algorithm to learn a discriminate local feature from the small patches of the face ima...

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: IEEE Access

سال: 2019

ISSN: 2169-3536

DOI: 10.1109/access.2019.2954693