Results 121 to 130 of about 245,952 (212)

EEG-TriNet++: A Transformer-Guided Meta-Learning Framework for Robust and Generalizable Motor Imagery Classification. [PDF]

Bioengineering (Basel)
Tibermacine A, Naidji I, Tibermacine IE, Mamen L, Rabehi A, Habib M.   +5 more
europepmc   +1 more source

Resource‐Aware Contrastive Scattering Meta‐Learning for Efficient Few‐Shot Acoustic Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley   +1 more source

Exploring Chemoinformatics Aspects of Few-Shot Meta-Learning by Example of an Infinite Dilution Activity Coefficient in Ionic Liquid Prediction. [PDF]

J Chem Inf Model
Baran K, Kloskowski A.
europepmc   +1 more source

A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing

Advanced Intelligent Systems, EarlyView.
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti, Weng Buxiu, Petr Trunin, Muhammad Sunny Nazeer, Lucia Beccai, Perla Maiolino, Cecilia Laschi   +6 more
wiley   +1 more source

Correction: A meta-learning-based robust federated learning for diagnosing lung adenocarcinoma and tuberculosis granulomas. [PDF]

Front Oncol
Chen Y, Liu L, Feng B, Chen Y, Xu J, Lin H, Li K, Chen X, Ke Y, Zhou H, Hu Q, Jin Q, Long W, Li Q, Chen X.   +14 more
europepmc   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source

EEG Cross-Subject Taste Classification Method: A Meta-Learning Wavelet Graph Convolutional Neural Network Under Sweet and Bitter Stimuli. [PDF]

Biosensors (Basel)
Wang H, Men H, Shi Y.
europepmc   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

Advanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source

Few-shot cross-domain fault diagnosis via adversarial meta-learning. [PDF]

Sci Rep
Guo Y, Dai J, Zhang J.
europepmc   +1 more source

Playing in the Dark: Invisible Chess as a Laboratory for Strategic AI

AI &Innovation, EarlyView.
This paper shows that strategic AI evaluated on perfect‐information benchmarks can be brittle in real adversarial settings. By using invisible chess as a benchmark for hidden state and deception, it argues for stricter testing, human oversight, and more cautious governance of high‐stakes AI systems.
Paolo Ciancarini
wiley   +1 more source