Results 191 to 200 of about 176,660 (282)
Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding. [PDF]
Fang C +4 more
europepmc +1 more source
Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang +12 more
wiley +1 more source
Early prediction of wind turbine anomalies using 1D-CNN and temporal feature engineering on multi-source SCADA data. [PDF]
Ata MM, Osama S, Ibraheem MR, Abas AR.
europepmc +1 more source
ABSTRACT Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm—the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal ...
Ruolan Leslie Famularo +3 more
wiley +1 more source
The legacy and future of recurrent neural networks in personalized medicine: A reflection on the 2024 Nobel Physics Prize. [PDF]
Wittrup E +4 more
europepmc +1 more source
ABSTRACT Automated detection and classification of marine mammal vocalizations is critical for conservation and management efforts but is hindered by limited annotated datasets and the acoustic complexity of real‐world marine environments. Data augmentation has proven to be an effective strategy to address this limitation by increasing dataset ...
Bruno Padovese +3 more
wiley +1 more source
The Use of DeepQSAR Models for the Discovery of Peptides With Enhanced Antimicrobial and Antibiofilm Potential. [PDF]
You J +5 more
europepmc +1 more source
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
Biologically informed cortical models predict optogenetic perturbations. [PDF]
Sourmpis C +3 more
europepmc +1 more source

