Results 31 to 40 of about 222,333 (116)

Fingerprint Liveness Detection in the Presence of Capable Intruders

Sensors, 2015
Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the
Ana F. Sequeira, Jaime S. Cardoso
doaj   +1 more source

Classification Algorithm and Application Based on Semi-Supervised Deep Auto-Encoder Network [PDF]

Jisuanji gongcheng
In industrial classification prediction, labeled data are scarce, and labeling is expensive, leading to inaccurate model predictions. Simultaneously, features in most unlabeled data are not effectively used, resulting in insufficient generalization of ...
ZHANG Xinbo, ZHANG Xueying, HUANG Lixia, CHEN Guijun
doaj   +1 more source

MalSSL—Self-Supervised Learning for Accurate and Label-Efficient Malware Classification

IEEE Access
Malware classification with supervised learning requires a large dataset, which needs an expensive and time-consuming labeling process. In this paper, we explore the efficacy of self-supervised learning techniques for malware classification.
Setia Juli Irzal Ismail, Hendrawan, Budi Rahardjo, Tutun Juhana, Yasuo Musashi   +4 more
doaj   +1 more source

SPEMix: a lightweight method via superclass pseudo-label and efficient mixup for echocardiogram view classification

Frontiers in Artificial Intelligence
IntroductionIn clinical, the echocardiogram is the most widely used for diagnosing heart diseases. Different heart diseases are diagnosed based on different views of the echocardiogram images, so efficient echocardiogram view classification can help ...
Shizhou Ma, Yifeng Zhang, Delong Li, Yixin Sun, Zhaowen Qiu, Lei Wei, Suyu Dong   +6 more
doaj   +1 more source

A Novel Object-Based Supervised Classification Method with Active Learning and Random Forest for PolSAR Imagery

Remote Sensing, 2018
Most of the traditional supervised classification methods using full-polarimetric synthetic aperture radar (PolSAR) imagery are dependent on sufficient training samples, whereas the results of pixel-based supervised classification methods show a high ...
Wensong Liu, Jie Yang, Pingxiang Li, Yue Han, Jinqi Zhao, Hongtao Shi   +5 more
doaj   +1 more source

Effectiveness of Semi-Supervised Learning and Multi-Source Data in Detailed Urban Landuse Mapping with a Few Labeled Samples

Remote Sensing, 2022
Detailed urban landuse information plays a fundamental role in smart city management. A sufficient sample size has been identified as a very crucial pre-request in machine learning algorithms for urban landuse classification.
Bo Sun, Yang Zhang, Qiming Zhou, Xinchang Zhang   +3 more
doaj   +1 more source

Tree Species Classification Based on Self-Supervised Learning with Multisource Remote Sensing Images

Applied Sciences, 2023
In order to solve the problem of manual labeling in semi-supervised tree species classification, this paper proposes a pixel-level self-supervised learning model named M-SSL (multisource self-supervised learning), which takes the advantage of the ...
Xueliang Wang, Nan Yang, Enjun Liu, Wencheng Gu, Jinglin Zhang, Shuo Zhao, Guijiang Sun, Jian Wang   +7 more
doaj   +1 more source

Research on semi-supervised multi-graph classification algorithm based on MR-MGSSL for sensor network

EURASIP Journal on Wireless Communications and Networking, 2020
With the advent of the era of network information, the amount of data in network information is getting larger and larger, and the classification of data becomes particularly important.
Yang Gang, Zhang Na, Jin Tao, Wang Dawei, Kang Yinzhu, Gao Feng   +5 more
doaj   +1 more source

Semi-supervised Remote Sensing Image Scene Classification Based on Generative Adversarial Networks

International Journal of Computational Intelligence Systems, 2022
With the availability of numerous high-resolution remote sensing images, remote sensing image scene classification has been widely used in various fields. Compared with the field of natural images, the insufficient number of labeled remote sensing images
Dongen Guo, Zechen Wu, Yuanzheng Zhang, Zhen Shen   +3 more
doaj   +1 more source

Label knowledge-guided heterogeneous graph contrastive learning for semi-supervised short text sentiment classification

Journal of Big Data
Semi-supervised classification demonstrates effective performance in categorizing short-length texts, such as social media posts and online reviews, through the utilization of limited labeled data.
Mingqiang Wu
doaj   +1 more source