Results 111 to 120 of about 160,235 (299)
Machine Learning Integrity and Privacy in Adversarial Environments [PDF]
, 2021 Alina Oprea
openalex +1 more source
Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining
Advanced Intelligent Systems, EarlyView.Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson +3 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Hallgrimson et al. introduce a machine learning algorithm, siMILe, that takes features of single‐molecule localization microscopy localization clusters (e.g., size and sphericity) and finds the clusters that are associated with certain cell conditions (such as differential protein expression or drug treatment).
Christian Hallgrimson +8 more
wiley +1 more source
A System-Driven Taxonomy of Attacks and Defenses in Adversarial Machine Learning. [PDF]
IEEE Trans Emerg Top Comput Intell, 2020 Sadeghi K, Banerjee A, Gupta SKS.
europepmc +1 more source
Adversarial Machine Learning in Wireless Communications Using RF Data: A Review [PDF]
, 2022 Damilola Adesina +3 more
openalex +1 more source
Adversarial and Secure Machine Learning.
, 2017 We present the state-of-art study of a recent emerging research area named as Adversarial Machine Learning, it investigates the vulnerabilities of current learning algorithms from the perspective of an adversary. We show that several state-of-art learning systems are intrinsically vulnerable under carefully designed adversarial attacks.
openaire +2 more sources
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 +6 more
wiley +1 more source
Defending Against Adversarial Machine Learning
CoRR, 2019 adversarial machine learning, accuracy, probability, feature mask, genetic algorithm, authorship attribution system ...
openaire +2 more sources
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 +5 more
wiley +1 more source