A survey of machine and deep learning methods for internet of things (IoT) security
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …
one another with minimal human intervention. IoT is one of the fastest developing fields in …
Ensemble learning: A survey
O Sagi, L Rokach - Wiley interdisciplinary reviews: data mining …, 2018 - Wiley Online Library
Ensemble methods are considered the state‐of‐the art solution for many machine learning
challenges. Such methods improve the predictive performance of a single model by training …
challenges. Such methods improve the predictive performance of a single model by training …
DeepSMOTE: Fusing deep learning and SMOTE for imbalanced data
D Dablain, B Krawczyk… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Despite over two decades of progress, imbalanced data is still considered a significant
challenge for contemporary machine learning models. Modern advances in deep learning …
challenge for contemporary machine learning models. Modern advances in deep learning …
[PDF][PDF] 高光谱遥感影像分类研究进展
杜培军， 夏俊士， 薛朝辉， 谭琨， 苏红军， 鲍蕊 - 遥感学报, 2021 - ygxb.ac.cn
随着模式识别, 机器学习, 遥感技术等相关学科领域的发展, 高光谱遥感影像分类研究取得快速
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …
A broad review on class imbalance learning techniques
S Rezvani, X Wang - Applied Soft Computing, 2023 - Elsevier
The imbalanced learning issue is related to the performance of learning algorithms in the
presence of asymmetrical class distribution. Due to the complex characteristics of …
presence of asymmetrical class distribution. Due to the complex characteristics of …
A review of intrusion detection systems using machine and deep learning in internet of things: Challenges, solutions and future directions
The Internet of Things (IoT) is poised to impact several aspects of our lives with its fast
proliferation in many areas such as wearable devices, smart sensors and home appliances …
proliferation in many areas such as wearable devices, smart sensors and home appliances …
TSE-IDS: A two-stage classifier ensemble for intelligent anomaly-based intrusion detection system
Intrusion detection systems (IDSs) play a pivotal role in computer security by discovering
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
Short-term rockburst prediction in underground project: Insights from an explainable and interpretable ensemble learning model
Rockburst is a frequent challenge during tunnel and other underground construction and is
an extreme rock damage phenomenon. Therefore, it is very crucial to accurately estimate the …
an extreme rock damage phenomenon. Therefore, it is very crucial to accurately estimate the …
Ensemble learning for data stream analysis: A survey
In many applications of information systems learning algorithms have to act in dynamic
environments where data are collected in the form of transient data streams. Compared to …
environments where data are collected in the form of transient data streams. Compared to …
[HTML][HTML] Learning from imbalanced data: open challenges and future directions
B Krawczyk - Progress in artificial intelligence, 2016 - Springer
Despite more than two decades of continuous development learning from imbalanced data
is still a focus of intense research. Starting as a problem of skewed distributions of binary …
is still a focus of intense research. Starting as a problem of skewed distributions of binary …