Results 191 to 200 of about 25,600 (268)

Temporal single spike coding for effective transfer learning in spiking neural networks. [PDF]

Sci Rep
Moqadasi H, Safari S, Mateo F.
europepmc   +1 more source

Computational intelligence model for predicting the compressive strength of FRP‐confined concrete column

Structural Concrete, EarlyView.
Abstract Fiber reinforced polymer (FRP) wrapping technology is commonly used to enhance the compressive strength (CS) of reinforced concrete (RC) members. Accurate prediction of the compressive strength of FRP‐confined concrete columns is crucial for optimizing structural design and helps reduce the time and costs associated with physical testing ...
XuanRui Yu, Nima Khodadadi, Anxiang Song, Tianyu Hu, Yang Yu, Antonio Nanni   +5 more
wiley   +1 more source

GRN+: a simplified generative reinforcement network for tissue layer analysis in 3D ultrasound images for chronic low-back pain. [PDF]

J Med Imaging (Bellingham)
Zeng Z, Zhao X, Cartier M, Meng X, Pu J.
europepmc   +1 more source

Reflections on the Future of Statistics Education in a Technological Era

Teaching Statistics, EarlyView.
ABSTRACT Keeping pace with rapidly evolving technology is a key challenge in teaching statistics. To equip students with essential skills for the modern workplace, educators must integrate relevant technologies into the statistical curriculum where possible.
Craig Alexander, Jennifer Gaskell, Vinny Davies   +2 more
wiley   +1 more source

Explainability Methods from Machine Learning Detect Important Drugs' Atoms in Drug-Target Interactions. [PDF]

J Chem Inf Model
Mahindran M, Liu Q, Kadambalithaya VM, Kalinina OV.   +3 more
europepmc   +1 more source

ECG‐TransCovNet: A hybrid transformer model for accurate arrhythmia detection using Electrocardiogram signals

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Abnormalities in the heart's rhythm, known as arrhythmias, pose a significant threat to global health, often leading to severe cardiac conditions and sudden cardiac deaths. Therefore, early and accurate detection of arrhythmias is crucial for timely intervention and potentially life‐saving treatment.
Hasnain Ali Shah, Faisal Saeed, Muhammad Diyan, Nouf Abdullah Almujally, Jae‐Mo Kang   +4 more
wiley   +1 more source

SE-SNN: Squeeze-and-Excitation-Enhanced Spiking Neural Networks with Learnable Neuron Dynamics for Event-Based Vision. [PDF]

Biomimetics (Basel)
Liu C, Chen Y.
europepmc   +1 more source

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

Three factor delay learning rules for spiking neural networks. [PDF]

Front Neurosci
Vassallo L, Taherinejad N.
europepmc   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng   +4 more
wiley   +1 more source