Results 171 to 180 of about 27,097 (268)

Cascade Deep Learning With Physics Guidance for Typhoon Intensity Prediction

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Typhoons pose a significant threat to both human safety and economic stability. As a crucial metric for assessing their destructive potential, typhoon intensity (TI) prediction has become an important research focus, with numerous methods developed.
Zhengya Sun   +4 more
wiley   +1 more source

Dissecting Glioma Heterogeneity: A Deep Hybrid Graph Convolutional Network With Hinge Attention for Causal‐Effect Explainability

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Brain tumour classification is a critical task in medical imaging that requires accurate and interpretable solutions to assist in clinical decision‐making. In this paper, we present GraphConvNet‐X, a novel hybrid model that integrates convolutional neural networks (CNNs) for spatial feature extraction with graph neural networks (GNNs) that ...
Sultanul Arifeen Hamim   +4 more
wiley   +1 more source

طریقة الـدمج بشبکة انتشار الخطأ خلفاً

open access: yesAl-Rafidain Journal of Computer Sciences and Mathematics, 2005
Nidhal H. Al-Assady   +2 more
doaj   +1 more source

TriadAuth: Continuous Authentication Through Structured GUI Sequence Modelling With Drift Adaptation and Modality‐Aware Explanations

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Continuous authentication (CA) systems based on behavioural biometrics are increasingly deployed in zero‐trust architectures, yet their performance degrades over time due to natural behavioural drift arising from device changes, fatigue and evolving habits.
Ahmed Alzahrani
wiley   +1 more source

A Validation Method for the Enhanced Fuzzy Min‐Max Neural Network With Application to Heart Disease Data Classification

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This study investigates early detection of heart diseases using a new Enhanced Fuzzy Min‐Max (EFMM) neural network. Two key modifications are introduced: a refined EFMM contraction procedure during the learning phase to reduce data distortion and information loss, and a new weighted validation method to optimise hyperbox selection and improve ...
Mohammed Falah Mohammed   +3 more
wiley   +1 more source

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