195   Artículos

 
en línea
Kenneth David Strang    
A critical worldwide problem is that ransomware cyberattacks can be costly to organizations. Moreover, accidental employee cybercrime risk can be challenging to prevent, even by leveraging advanced computer science techniques. This exploratory project us... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Min Ma, Shanrong Liu, Shufei Wang and Shengnan Shi    
Automatic modulation classification (AMC) plays a crucial role in wireless communication by identifying the modulation scheme of received signals, bridging signal reception and demodulation. Its main challenge lies in performing accurate signal processin... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Rui Zhang, Mingwei Yao, Zijie Qiu, Lizhuo Zhang, Wei Li and Yue Shen    
Wheat breeding heavily relies on the observation of various traits during the wheat growth process. Among all traits, wheat head density stands out as a particularly crucial characteristic. Despite the realization of high-throughput phenotypic data colle... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Jie Wang, Jie Yang, Jiafan He and Dongliang Peng    
Semi-supervised learning has been proven to be effective in utilizing unlabeled samples to mitigate the problem of limited labeled data. Traditional semi-supervised learning methods generate pseudo-labels for unlabeled samples and train the classifier us... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Adam Olesinski and Zbigniew Piotrowski    
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu    
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Dongming Wang, Li Xu, Wei Gao, Hongwei Xia, Ning Guo and Xiaohan Ren    
As an extremely important energy source, improving the efficiency and accuracy of coal classification is important for industrial production and pollution reduction. Laser-induced breakdown spectroscopy (LIBS) is a new technology for coal classification ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yugen Yi, Haoming Zhang, Ningyi Zhang, Wei Zhou, Xiaomei Huang, Gengsheng Xie and Caixia Zheng    
As the feature dimension of data continues to expand, the task of selecting an optimal subset of features from a pool of limited labeled data and extensive unlabeled data becomes more and more challenging. In recent years, some semi-supervised feature se... ver más
Revista: Information    Formato: Electrónico

 
en línea
Jie Zhang, Fan Li, Xin Zhang, Yue Cheng and Xinhong Hei    
As a crucial task for disease diagnosis, existing semi-supervised segmentation approaches process labeled and unlabeled data separately, ignoring the relationships between them, thereby limiting further performance improvements. In this work, we introduc... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yang Zhang, Yuan Feng, Shiqi Wang, Zhicheng Tang, Zhenduo Zhai, Reid Viegut, Lisa Webb, Andrew Raedeke and Yi Shang    
Waterfowl populations monitoring is essential for wetland conservation. Lately, deep learning techniques have shown promising advancements in detecting waterfowl in aerial images. In this paper, we present performance evaluation of several popular superv... ver más
Revista: Information    Formato: Electrónico

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