Results 91 to 100 of about 83,974 (281)

Multi-Variable Transformer-Based Meta-Learning for Few-Shot Fault Diagnosis of Large-Scale Systems

Sensors
Fault diagnosis in large-scale systems presents significant challenges due to the complexity and high dimensionality of data, as well as the scarcity of labeled fault data, which are hard to obtain during the practical operation process.
Weiyang Li, Yixin Nie, Fan Yang
doaj   +1 more source

Video‐based diagnostics supported by artificial intelligence as an opportunity to address the epilepsy diagnostic gap: A narrative review

Epilepsia, EarlyView.
Abstract Despite advancements in epilepsy care, a substantial diagnostic gap persists, particularly in resource‐limited settings. This narrative review explores the potential of video‐based diagnostics augmented by artificial intelligence (AI) to address this gap by enabling earlier and more accessible seizure detection and classification.
Gadi Miron, Robert Terziev, Maximilian Schöls, John McLaren, Tobias Loddenkemper, Jörg Wellmer, Sigrid Mues, Christian Meisel   +7 more
wiley   +1 more source

Comparing Transcriptomic Responses to Chemicals Across Six Species Using the EcoToxChip RNASeq Database

Environmental Toxicology and Chemistry, EarlyView.
Abstract The EcoToxChip project includes RNA‐sequencing data from experiments involving model (Japanese quail, fathead minnow, African clawed frog) and ecological (double‐crested cormorant, rainbow trout, northern leopard frog) species at multiple life stages (whole embryo and adult) exposed to eight chemicals of environmental concern known to perturb ...
Krittika Mittal, Jessica Ewald, Doug Crump, Jessica Head, Markus Hecker, Natacha Hogan, Jianguo Xia, Niladri Basu   +7 more
wiley   +1 more source

Meta-Transformers: A Hybrid Approach for Medical Image Segmentation With U-Net and Meta-Learning

IEEE Access
The increasing demand for accurate and efficient medical image segmentation has driven the development of advanced Artificial Intelligence (AI) models to assist in diagnosing and planning treatments.
Neha Tirpude, Tausif Diwan, Meera Dhabu
doaj   +1 more source

Privacy Challenges in Meta-Learning: An Investigation on Model-Agnostic Meta-Learning

Meta-learning involves multiple learners, each dedicated to specific tasks, collaborating in a data-constrained setting. In current meta-learning methods, task learners locally learn models from sensitive data, termed support sets. These task learners subsequently share model-related information, such as gradients or loss values, which is computed ...
Rafiei, Mina, Maheri, Mohammadmahdi, Rabiee, Hamid R.   +2 more
openaire   +2 more sources

Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation

, 2019
Model-agnostic meta-learners aim to acquire meta-learned parameters from similar tasks to adapt to novel tasks from the same distribution with few gradient updates. With the flexibility in the choice of models, those frameworks demonstrate appealing performance on a variety of domains such as few-shot image classification and reinforcement learning ...
Vuorio, Risto, Sun, Shao-Hua, Hu, Hexiang, Lim, Joseph J.   +3 more
openaire   +2 more sources

Wonder as a Gateway to Science Meaning‐Making: Primary Pupils’ Narrative Journeys

Future in Educational Research, EarlyView.
ABSTRACT This study explores how wonder fosters transformative learning in science education for pupils (11–12 years old), creating meaning about cycles in nature. As an emotional and epistemic trigger, wonder may bridge everyday experiences with abstract scientific concepts by stimulating curiosity and creativity. Through a narrative writing task, the
Pauline Book, Siri‐Christine Seehuus
wiley   +1 more source

Metalinguist: enhancing hate speech detection with cross-lingual meta-learning

Complex & Intelligent Systems
The rise of social media has led to an increase in hate speech. Hate speech is generally described as a deliberate act of aggression aimed at a particular group, intended to harm or marginalize them based on specific attributes of their identity.
Ehtesham Hashmi, Sule Yildirim Yayilgan, Mohamed Abomhara   +2 more
doaj   +1 more source

The Case of Fleeting Orders and Flickering Quotes

Journal of Futures Markets, EarlyView.
ABSTRACT The literature controversially discusses the ambiguous motives and driving forces behind quickly cancelled limit orders (fleeting orders), which are characteristic of high‐frequency markets. In particular, manipulative and dysfunctional characteristics are feared. We analyze top‐of‐book fleeting orders—so‐called flickering quotes—and show with
Markus Ulze, Johannes Stadler, Andreas W. Rathgeber   +2 more
wiley   +1 more source

Predicting Major Depression Among Diverse Online Gamers: The Role of Internet Addiction and Spirituality

Journal of Addictions &Offender Counseling, EarlyView.
ABSTRACT This study analyzed whether religious or spiritual affiliation and therapy enrollment protect against symptoms meeting Major Depressive Disorder criteria beyond demographic, Internet addiction, and described therapy enrollment. Findings illustrated one risk factor and one protective factor associated with experiencing symptoms that meet Major ...
Lindsay A. Lundeen, John R. McCall
wiley   +1 more source