Results 81 to 90 of about 8,328,816 (311)

Continual Learning for Multimodal Data Fusion of a Soft Gripper

open access: yesAdvanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Gaussian mixture variational autoencoder for collaborative filtering

open access: yes四川大学学报. 自然科学版, 2023
Currently, machine learning-based detectors are widely used to handle millions of Android malware, but they often suffer from poor anti-adversarial attack abilities.
ZHANG Yu-Ke, WANG Jun-Feng
doaj  

Pemanfaatan Deep Convolutional Auto-encoder untuk Mitigasi Serangan Adversarial Attack pada Citra Digital

open access: yesJournal of Information and Technology, 2023
Serangan adversarial pada citra digital merupakan ancaman serius bagi penggunaan teknologi machine learning dalam berbagai aplikasi kehidupan sehari-hari. Teknik Fast Gradient Sign Method (FGSM) telah terbukti efektif dalam melakukan serangan pada model
Putu Widiarsa Kurniawan S   +2 more
doaj   +1 more source

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

open access: yesAdvanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi   +2 more
wiley   +1 more source

Adversarial Machine Learning Based Partial-model Attack in IoT

open access: yes, 2020
As Internet of Things (IoT) has emerged as the next logical stage of the Internet, it has become imperative to understand the vulnerabilities of the IoT systems when supporting diverse applications.
Lu, Zhuo   +5 more
core   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

open access: yesAdvanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao   +6 more
wiley   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

open access: yesAdvanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown   +3 more
wiley   +1 more source

How to beat a Bayesian adversary

open access: yesEuropean Journal of Applied Mathematics
Deep neural networks and other modern machine learning models are often susceptible to adversarial attacks. Indeed, an adversary may often be able to change a model’s prediction through a small, directed perturbation of the model’s input – an issue in ...
Zihan Ding   +3 more
doaj   +1 more source

Enhancing adversarial robustness of quantum neural networks by adding noise layers

open access: yesNew Journal of Physics, 2023
The rapid advancements in machine learning and quantum computing have given rise to a new research frontier: quantum machine learning. Quantum models designed for tackling classification problems possess the potential to deliver speed enhancements and ...
Chenyi Huang, Shibin Zhang
doaj   +1 more source

Adversarial support vector machine learning [PDF]

open access: yesProceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 2012
Many learning tasks such as spam filtering and credit card fraud detection face an active adversary that tries to avoid detection. For learning problems that deal with an active adversary, it is important to model the adversary's attack strategy and develop robust learning models to mitigate the attack. These are the two objectives of this paper.
Yan Zhou 0001   +3 more
openaire   +2 more sources

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