Zobrazeno 1 - 10
of 59 337
pro vyhledávání: '"Classifier (UML)"'
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:6969-6983
The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model label dependencies to improve recognition performance. To capture and explore
Publikováno v:
IEEE Transactions on Mobile Computing. 22:2520-2536
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:1406-1417
Relation classification (RC) task is one of fundamental tasks of information extraction, aiming to detect the relation information between entity pairs in unstructured natural language text and generate structured data in the form of entity-relation
Autor:
Yuria Saito, Kanako C. Hatanaka, Ayae Nange, Mitsuru Taniguchi, Keisuke Yamagishi, Yoshihiro Matsuno, Asami Okumura, Kengo Hamasaki, Yutaka Hatanaka, Hiroko Yamashita
Publikováno v:
Anticancer Research. 43:707-711
Background A subset of patients with estrogen receptor (ER)-positive, HER2-negative, and node-negative breast cancer experience recurrences. Predicting patients who will have recurrences within 5 years of surgery is essential so that patients can be
Publikováno v:
Materials Today: Proceedings. 80:3594-3599
Face recognition is one of the useful tasks and can be used for many applications as security systems, it is necessary to find effective and low complexity facial classifier methods. In this paper, we proposed a new one-dimensional CNN deep convoluti
Publikováno v:
Materials Today: Proceedings. 80:2684-2696
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:6749-6762
In this article, we propose a structure-aligned generative adversarial network framework to improve zero-shot learning (ZSL) by mitigating the semantic gap, domain shift, and hubness problem. The proposed framework contains two parts, i.e., a generat
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:6737-6748
Network embedding (NE) aims to encode the relations of vertices into a low-dimensional space. After NE, we can obtain the learned vectors of vertices that preserve the proximity of network structures for subsequent applications, e.g., vertex classifi
Autor:
Qingyao Wu, Yuzhong Ye, Hanrui Wu, Liu Dapeng, Min Lu, Yuguang Yan, Bi Chaoyang, Michael K. Ng
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:5536-5551
Domain adaptation aims at extracting knowledge from auxiliary source domains to assist the learning task in a target domain. In classification problems, since the distributions of the source and target domains are different, directly using source dat
Publikováno v:
Journal of King Saud University - Computer and Information Sciences. 34:6883-6894
Security issues in mobile apps are increasingly relevant as this software have become part of the daily life of billions of people. As the dominant OS, Android is a primary target for ill-intentioned programmers willing to exploit its vulnerabilities