Results 141 to 150 of about 219,753 (266)

A Gradual Adversarial Training Method for Semantic Segmentation

Remote Sensing
Deep neural networks (DNNs) have achieved great success in various computer vision tasks. However, they are susceptible to artificially designed adversarial perturbations, which limit their deployment in security-critical applications.
Yinkai Zan, Pingping Lu, Tingyu Meng
doaj   +1 more source

Feature separation and adversarial training for the patient-independent detection of epileptic seizures. [PDF]

Front Comput Neurosci, 2023
Yang Y, Li F, Qin X, Wen H, Lin X, Huang D.   +5 more
europepmc   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Between-Class Adversarial Training for Improving Adversarial Robustness of Image Classification. [PDF]

Sensors (Basel), 2023
Wang D, Jin W, Wu Y.
europepmc   +1 more source

An Intelligent Feature Engineering‐Driven Hybrid Framework for Adversarial Domain Name System Tunneling Detection

Advanced Intelligent Systems, EarlyView.
This study presents a novel framework that enhances the reliability of DNS traffic monitoring using a hybrid long short‐term memory‐deep neural network (LSMT‐DNN) architecture, enabling robust detection of adversarial DNS tunneling. The proposed framework leverages feature extraction from DNS traffic patterns, including domain request sequences, query ...
Ahmad Almadhor, Shtwai Alsubai, Monji Mohamed Zaidi, Natalia Kryvinska, Abdullah Al Hejaili, Sidra Abbas   +5 more
wiley   +1 more source

An adversarial training framework for mitigating algorithmic biases in clinical machine learning. [PDF]

NPJ Digit Med, 2023
Yang J, Soltan AAS, Eyre DW, Yang Y, Clifton DA.   +4 more
europepmc   +1 more source

SCP‐Pose: Leveraging Structural Consistency Prior Knowledge for Real‐Time Category‐Level 6D Pose Estimation

Advanced Intelligent Systems, EarlyView.
This paper presents a high‐speed object pose estimation method that deconstructs objects into geometric components. Inspired by human cognitive generalization, it detects these primitives and infers the 6D pose from their stable spatial configuration.
Xuyang Li, Mingxuan Yu, Xuemei Xie, Zhaozhuo An, Qiyue Li, Xiaodan Song, Guangming Shi   +6 more
wiley   +1 more source

Privacy-Aware Early Detection of COVID-19 Through Adversarial Training. [PDF]

IEEE J Biomed Health Inform, 2023
Rohanian O, Kouchaki S, Soltan A, Yang J, Rohanian M, Yang Y, Clifton D.   +6 more
europepmc   +1 more source

OntoLogX: Ontology‐Guided Knowledge Graph Extraction From Cybersecurity Logs With Large Language Models

Advanced Intelligent Systems, EarlyView.
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti, Idilio Drago, Anisa Rula, Devis Bianchini, Federico Cerutti   +4 more
wiley   +1 more source

Named entity recognition for Chinese based on global pointer and adversarial training. [PDF]

Sci Rep, 2023
Li H, Cheng M, Yang Z, Yang L, Chua Y.
europepmc   +1 more source