Artificial intelligence systems for tool condition monitoring in machining: Analysis and critical review
The wear of cutting tools, cutting force determination, surface roughness variations and other
machining responses are of keen interest to latest researchers. The variations of these …
machining responses are of keen interest to latest researchers. The variations of these …
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 …
Towards understanding ensemble, knowledge distillation and self-distillation in deep learning
Z Allen-Zhu, Y Li - arXiv preprint arXiv:2012.09816, 2020 - arxiv.org
We formally study how ensemble of deep learning models can improve test accuracy, and
how the superior performance of ensemble can be distilled into a single model using …
how the superior performance of ensemble can be distilled into a single model using …
[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 …
From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0
Abstract The Internet of Things (IoT), Big Data and Machine Learning (ML) may represent
the foundations for implementing the concept of intelligent production, smart products …
the foundations for implementing the concept of intelligent production, smart products …
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 …
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 …
CHAOS challenge-combined (CT-MR) healthy abdominal organ segmentation
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research
field for many years. In the last decade, intensive developments in deep learning (DL) …
field for many years. In the last decade, intensive developments in deep learning (DL) …
Ensembles for feature selection: A review and future trends
V Bolón-Canedo, A Alonso-Betanzos - Information fusion, 2019 - Elsevier
Ensemble learning is a prolific field in Machine Learning since it is based on the assumption
that combining the output of multiple models is better than using a single model, and it …
that combining the output of multiple models is better than using a single model, and it …
Deep multimodal learning: A survey on recent advances and trends
D Ramachandram, GW Taylor - IEEE signal processing …, 2017 - ieeexplore.ieee.org
The success of deep learning has been a catalyst to solving increasingly complex machine-
learning problems, which often involve multiple data modalities. We review recent advances …
learning problems, which often involve multiple data modalities. We review recent advances …