SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training. [PDF]
Huang W +5 more
europepmc +1 more source
Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition. [PDF]
Lal S +7 more
europepmc +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Chinese medical named entity recognition integrating adversarial training and feature enhancement. [PDF]
Zhang X +6 more
europepmc +1 more source
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization. [PDF]
Han T +10 more
europepmc +1 more source
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan +4 more
wiley +1 more source
Adversarial training with misaligned label correction for carotid segmentation from simultaneous non-contrast angiography and intraplaque hemorrhage MRI. [PDF]
Zhang W, Lin M, Chan KL, Chen H, Chiu B.
europepmc +1 more source
Fast Adversarial Training against Textual Adversarial Attacks
Many adversarial defense methods have been proposed to enhance the adversarial robustness of natural language processing models. However, most of them introduce additional pre-set linguistic knowledge and assume that the synonym candidates used by attackers are accessible, which is an ideal assumption.
Yang, Yichen, Liu, Xin, He, Kun
openaire +1 more source
Prediction of Pipeline Defect Depth and Classification Based on CatBoost
Obtaining detection data using in‐line pipeline inspection, the synthetic minority oversampling technique (SMOTE) is applied to expand the sample set, thereby increasing the number of minority‐class samples. This approach effectively improves minority‐class detection and enhances pipeline safety assessment. ABSTRACT Magnetic flux leakage detection is a
Cong Chen +3 more
wiley +1 more source
GAN‐LSTM‐3D: An efficient method for lung tumour 3D reconstruction enhanced by attention‐based LSTM
Abstract Three‐dimensional (3D) image reconstruction of tumours can visualise their structures with precision and high resolution. In this article, GAN‐LSTM‐3D method is proposed for 3D reconstruction of lung cancer tumours from 2D CT images. Our method consists of three phases: lung segmentation, tumour segmentation, and tumour 3D reconstruction. Lung
Lu Hong +12 more
wiley +1 more source

