Results 1 to 10 of about 8,068,470 (297)
Survey of Multi-label Classification Based on Supervised and Semi-supervised Learning [PDF]
Jisuanji kexue, 2022 Most of the traditional multi-label classification algorithms use supervised learning,but in real life,there are many unlabeled data.Manual tagging of all required data is costly.Semi-supervised learning algorithms can work with a large amount of ...
WU Hong-xin, HAN Meng, CHEN Zhi-qiang, ZHANG Xi-long, LI Mu-hang
doaj +1 more source
OBJECT DETECTION USING SEMI SUPERVISED LEARNING METHODS
ICTACT Journal on Soft Computing, 2022 Object detection is used to identify objects in real time using some deep learning algorithms. In this work, wheat plant data set around the world is collected to study the wheat heads.
Shymala Gowri Selvaganapathy +3 more
doaj +1 more source
Classification Uncertainty Minimization-based Semi-supervised Ensemble Learning Algorithm [PDF]
Jisuanji kexue, 2023 Semi-supervised ensemble learning(SSEL) is a combinatorial paradigm by fusing semi-supervised learning and ensemble learning together,which improves the diversity of ensemble learning by introducing unlabeled samples and at the same time solves the ...
HE Yulin, ZHU Penghui, HUANG Zhexue, Fournier-Viger PHILIPPE
doaj +1 more source
An Improved Algorithm of Drift Compensation for Olfactory Sensors
Applied Sciences, 2022 This research mainly studies the semi-supervised learning algorithm of different domain data in machine olfaction, also known as sensor drift compensation algorithm.
Siyu Lu +6 more
doaj +1 more source
Semi-supervised Learning on Graphs Using Adversarial Training with Generated Sample [PDF]
Jisuanji kexue yu tansuo, 2023 Given a graph composed of a small number of labeled nodes and a large number of unlabeled nodes, semi-supervised learning on graphs aims to assign labels for the unlabeled nodes.
WANG Cong, WANG Jie, LIU Quanming, LIANG Jiye
doaj +1 more source
Semi-supervised Object Detection with Sequential Three-way Decision [PDF]
Jisuanji kexue, 2023 The need for large scale data in deep learning and the complexity of object detection annotation task promote the deve-lopment of semi-supervised object detection.In recent years,semi-supervised object detection has achieved many excellent results ...
SONG Faxing, MIAO Duoqian, ZHANG Hongyun
doaj +1 more source
A survey of large-scale graph-based semi-supervised classification algorithms
International Journal of Cognitive Computing in Engineering, 2022 Semi-supervised learning is an effective method to study how to use both labeled data and unlabeled data to improve the performance of the classifier, which has become the hot field of machine learning in recent years.
Yunsheng Song, Jing Zhang, Chao Zhang
doaj +1 more source
Meta-Semi: A Meta-Learning Approach for Semi-Supervised Learning
CAAI Artificial Intelligence Research, 2022 Deep learning based semi-supervised learning (SSL) algorithms have led to promising results in recent years. However, they tend to introduce multiple tunable hyper-parameters, making them less practical in real SSL scenarios where the labeled data is ...
Yulin Wang +5 more
doaj +1 more source
International Journal of Applied Mathematics and Computer Science, 2023 Acoustic features of speech are promising as objective markers for mental health monitoring. Specialized smartphone apps can gather such acoustic data without disrupting the daily activities of patients.
Casalino Gabriella +6 more
doaj +1 more source
Information, 2021 Smart grids integrate advanced information and communication technologies (ICTs) into traditional power grids for more efficient and resilient power delivery and management, but also introduce new security vulnerabilities that can be exploited by ...
Ruobin Qi +3 more
doaj +1 more source