Results 71 to 80 of about 1,662,189 (295)

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

open access: yesAdvanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz   +5 more
wiley   +1 more source

Detecting adversarial examples of text

open access: yes, 2021
Although deep neural networks have achieved state-of-the-art performance in various tasks, a lot of their decisions are non-interpretable because high dimensional feature vectors cause deep neural net functions to be extremely difficult to visualize ...
Na Liu (10562882)
core   +1 more source

Assessing Optimizer Impact on DNN Model Sensitivity to Adversarial Examples

open access: yesIEEE Access, 2019
Deep Neural Networks (DNNs) have been gaining state-of-the-art achievement compared with many traditional Machine Learning (ML) models in diverse fields. However, adversarial examples challenge the further deployment and application of DNNs. Analysis has
Yixiang Wang   +5 more
doaj   +1 more source

On‐Chip Photonic Neural Network Architectures

open access: yesAdvanced Optical Materials, EarlyView.
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong   +7 more
wiley   +1 more source

About the inevitability of adversarial examples

open access: yes, 2019
Adversarial examples are a burring issue for deep learning.Yet, the basic definition of adversarial example is not that trivial.Indeed, if one consider adversarial examples as points close to decision boundary, then, one can prove that adversarial ...
Chan-Hon-Tong, Adrien
core   +2 more sources

A Novel Adversarial Example Detection Method Based on Frequency Domain Reconstruction for Image Sensors

open access: yesSensors
Convolutional neural networks (CNNs) have been extensively used in numerous remote sensing image detection tasks owing to their exceptional performance.
Shuaina Huang, Zhiyong Zhang, Bin Song
doaj   +1 more source

Information Transmission Strategies for Self‐Organized Robotic Aggregation

open access: yesAdvanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng   +5 more
wiley   +1 more source

Transferability Ranking of Adversarial Examples

open access: yesCoRR, 2022
Adversarial transferability in black-box scenarios presents a unique challenge: while attackers can employ surrogate models to craft adversarial examples, they lack assurance on whether these examples will successfully compromise the target model. Until now, the prevalent method to ascertain success has been trial and error-testing crafted samples ...
Levy, Mosh   +3 more
openaire   +2 more sources

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

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

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