Results 1 to 10 of about 8,974 (165)

Few-shot crop disease recognition using sequence- weighted ensemble model-agnostic meta-learning [PDF]

Frontiers in Plant Science
Diseases pose significant threats to crop production, leading to substantial yield reductions and jeopardizing global food security. Timely and accurate detection of crop diseases is essential for ensuring sustainable agricultural development and ...
Junlong Li, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang   +5 more
doaj   +2 more sources

Meta-learning provides a robust framework to discern taxonomic carnivore agency from the analysis of tooth marks on bone: reassessing the role of felids as predators of Homo habilis [PDF]

Royal Society Open Science
Determining carnivore agency in taphonomic research is crucial for identifying site formation processes and carnivore–hominin interactions that influenced human evolution.
Manuel Domínguez-Rodrigo, Gabriel Cifuentes-Alcobendas, Marina Vegara-Riquelme, Edgard Camarós, Enrique Baquedano   +4 more
doaj   +2 more sources

Eternal-MAML: a meta-learning framework for cross-domain defect recognition [PDF]

PeerJ Computer Science
Defect recognition tasks for industrial product suffer from a serious lack of samples, greatly limiting the generalizability of deep learning models. Addressing the imbalance of defective samples often involves leveraging pre-trained models for transfer ...
Jipeng Feng, Haigang Zhang, Zhifeng Wang
doaj   +3 more sources

Cellular Distribution and Motion of Essential Magnetosome Proteins Expressed in Mammalian Cells [PDF]

Biosensors
Magnetosomes are organelle-like structures within magnetotactic bacteria that store iron biominerals in membrane-bound vesicles. In bacteria, formation of these structures is highly regulated by approximately 30 genes, which are conserved throughout ...
Qin Sun, Cécile Fradin, Moeiz Ahmed, R. Terry Thompson, Frank S. Prato, Donna E. Goldhawk   +5 more
doaj   +2 more sources

A lightweight deep neural network for personalized detecting ventricular arrhythmias from a single-lead ECG device. [PDF]

PLOS Digital Health
Ventricular arrhythmia (VA) is a leading cause of sudden cardiac death. Detecting VA from electrocardiograms (ECGs) using deep learning techniques has potential to improve clinical outcomes.
Zhejun Sun, Wenrui Zhang, Yuxi Zhou, Shijia Geng, Deyun Zhang, Jiaze Wang, Bin Liu, Zhaoji Fu, Linlin Zheng, Chenyang Jiang, Guigang Zhang, Shenda Hong   +11 more
doaj   +2 more sources

Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation. [PDF]

PLoS ONE
IntroductionSleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This highlights
Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee   +4 more
doaj   +2 more sources

TCN-MAML: A TCN-Based Model with Model-Agnostic Meta-Learning for Cross-Subject Human Activity Recognition [PDF]

Sensors
Human activity recognition (HAR) using Wi-Fi-based sensing has emerged as a powerful, non-intrusive solution for monitoring human behavior in smart environments. Unlike wearable sensor systems that require user compliance, Wi-Fi channel state information
Chih-Yang Lin, Chia-Yu Lin, Yu-Tso Liu, Yi-Wei Chen, Hui-Fuang Ng, Timothy K. Shih   +5 more
doaj   +2 more sources

Essential magnetosome proteins MamI and MamL from magnetotactic bacteria interact in mammalian cells [PDF]

Scientific Reports
To detect cellular activities deep within the body using magnetic resonance platforms, magnetosomes are the ideal model of genetically-encoded nanoparticles. These membrane-bound iron biominerals produced by magnetotactic bacteria are highly regulated by
Qin Sun, Liu Yu, Sarah C. Donnelly, Cécile Fradin, R. Terry Thompson, Frank S. Prato, Donna E. Goldhawk   +6 more
doaj   +2 more sources

An Adaptive Framework for Intrusion Detection in IoT Security Using MAML (Model-Agnostic Meta-Learning) [PDF]

Sensors
With the rapid emergence of the Internet of Things (IoT) devices, there were new vectors for attacking cyber, so there was a need for approachable intrusion detection systems (IDSs) with more innovative custom tactics.
Fatma S. Alrayes, Syed Umar Amin, Nada Hakami   +2 more
doaj   +2 more sources

Ensemble-Based Model-Agnostic Meta-Learning with Operational Grouping for Intelligent Sensory Systems [PDF]

Sensors
Model-agnostic meta-learning (MAML), coupled with digital twins, is transformative for predictive maintenance (PdM), especially in robotic arms in assembly lines, where rapid and accurate fault classification of arms is essential.
Mainak Mallick, Young-Dae Shim, Hong-In Won, Seung-Kyum Choi   +3 more
doaj   +2 more sources