Cyber security intrusion detection for agriculture 4.0: Machine learning-based solutions, datasets, and future directions
In this paper, we review and analyze intrusion detection systems for Agriculture 4.0 cyber
security. Specifically, we present cyber security threats and evaluation metrics used in the …
security. Specifically, we present cyber security threats and evaluation metrics used in the …
Chimera: efficiently training large-scale neural networks with bidirectional pipelines
Training large deep learning models at scale is very challenging. This paper proposes
Chimera, a novel pipeline parallelism scheme which combines bidirectional pipelines for …
Chimera, a novel pipeline parallelism scheme which combines bidirectional pipelines for …
Why globally re-shuffle? Revisiting data shuffling in large scale deep learning
Stochastic gradient descent (SGD) is the most prevalent algorithm for training Deep Neural
Networks (DNN). SGD iterates the input data set in each training epoch processing data …
Networks (DNN). SGD iterates the input data set in each training epoch processing data …
Privacy and security in distributed learning: A review of challenges, solutions, and open research issues
In recent years, the way that machine learning is used has undergone a paradigm shift
driven by distributed and collaborative learning. Several approaches have emerged to …
driven by distributed and collaborative learning. Several approaches have emerged to …
A novel approach for fraud detection in blockchain-based healthcare networks using machine learning
Recently, the advent of blockchain (BC) has sparked a digital revolution in different fields,
such as finance, healthcare, and supply chain. It is used by smart healthcare systems to …
such as finance, healthcare, and supply chain. It is used by smart healthcare systems to …
Assessment of Six Machine Learning Methods for Predicting Gross Primary Productivity in Grassland
H Wang, W Shao, Y Hu, W Cao, Y Zhang - Remote Sensing, 2023 - mdpi.com
Grassland gross primary productivity (GPP) is an important part of global terrestrial carbon
flux, and its accurate simulation and future prediction play an important role in …
flux, and its accurate simulation and future prediction play an important role in …
Classification of plug seedling quality by improved convolutional neural network with an attention mechanism
X Du, L Si, X Jin, P Li, Z Yun, K Gao - Frontiers in Plant Science, 2022 - frontiersin.org
The classification of plug seedling quality plays an active role in enhancing the quality of
seedlings. The EfficientNet-B7-CBAM model, an improved convolutional neural network …
seedlings. The EfficientNet-B7-CBAM model, an improved convolutional neural network …
Qualitative survey on artificial intelligence integrated blockchain approach for 6G and beyond
Utilizing the 0.1 to 10 THz spectrum in the next-generation wireless communication networks
holds potential for futuristic applications. However, managing resources to accommodate …
holds potential for futuristic applications. However, managing resources to accommodate …
Research Trends and Development Dynamics of qPCR-based Biomarkers: A Comprehensive Bibliometric Analysis
L Liu, BR Mu, Y Zhou, QL Wu, B Li, DM Wang… - Molecular …, 2025 - Springer
Quantitative polymerase chain reaction (qPCR) is a vital molecular technique for biomarker
detection; however, its clinical application is impeded by the scarcity of robust biomarkers …
detection; however, its clinical application is impeded by the scarcity of robust biomarkers …
Learningchain. A novel blockchain-based meritocratic marketplace for training distributed machine learning models
E Zanardo - Proceedings of the Computational Methods in Systems …, 2022 - Springer
Beez blockchain is a decentralized AI model network that encourages peer collaboration to
improve machine learning accuracy. It'sa peer-to-peer network where peers can submit …
improve machine learning accuracy. It'sa peer-to-peer network where peers can submit …