|
|
|
|
|
Yunia Reyes González, Alfonso Claro Arceo, Natalia Martínez Sánchez, Antonio Hernández Domínguez
Pág. 82 - 96
Solving a problem leads to a process of identification and selection of the appropriate route for it solution. This process is called Decision Making, where a decision is choosing one among several alternatives. The basis of the decision-making process i...
ver más
|
|
|
|
|
|
|
|
|
|
|
Haidi Badr, Nayer Wanas and Magda Fayek
Unsupervised domain adaptation (UDA) presents a significant challenge in sentiment analysis, especially when faced with differences between source and target domains. This study introduces Weighted Sequential Unsupervised Domain Adaptation (WS-UDA), a no...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dania Tamayo-Vera, Xiuquan Wang and Morteza Mesbah
The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic domain is pivotal for addressing the multifaceted challenges posed by climate change on agriculture. This paper embarks on a systematic review to dissect the current ut...
ver más
|
|
|
|
|
|
|
|
|
|
|
Maryam Badar and Marco Fisichella
Fairness-aware mining of data streams is a challenging concern in the contemporary domain of machine learning. Many stream learning algorithms are used to replace humans in critical decision-making processes, e.g., hiring staff, assessing credit risk, et...
ver más
|
|
|
|
|
|
|
|
|
|
|
Longde Wang, Hui Cao, Zhichao Cui and Zeren Ai
Marine engines confront challenges of varying working conditions and intricate failures. Existing studies have primarily concentrated on fault diagnosis in a single condition, overlooking the adaptability of these methods in diverse working condition. To...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiaodong Cui, Zhuofan He, Yangtao Xue, Keke Tang, Peican Zhu and Jing Han
Underwater Acoustic Target Recognition (UATR) plays a crucial role in underwater detection devices. However, due to the difficulty and high cost of collecting data in the underwater environment, UATR still faces the problem of small datasets. Few-shot le...
ver más
|
|
|
|
|
|
|
|
|
|
|
Samira Ardani, Saeed Eftekhar Azam and Daniel G. Linzell
Transfer Learning (TL) in structural health monitoring is used for generalizing the trained knowledge for damage identification of a group of similar structures. TL significantly reduces the computational cost associated with retraining Machine Learning ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yeong-Hyeon Byeon and Keun-Chang Kwak
When acquiring electrocardiogram (ECG) signals, the placement of electrode patches is crucial for acquiring electrocardiographic signals. Constant displacement positions are essential for ensuring the consistency of the ECG signal when used for individua...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xinyi Liu, Baofeng Zhang and Na Liu
Both transformer and one-stage detectors have shown promising object detection results and have attracted increasing attention. However, the developments in effective domain adaptive techniques in transformer and one-stage detectors still have not been w...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhigang Song, Daisong Li, Zhongyou Chen and Wenqin Yang
The unsupervised domain-adaptive vehicle re-identification approach aims to transfer knowledge from a labeled source domain to an unlabeled target domain; however, there are knowledge differences between the target domain and the source domain. To mitiga...
ver más
|
|
|
|
|
|