Results 101 to 110 of about 1,132,463 (302)

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Adversarial attacks and defenses for digital communication signals identification

Digital Communications and Networks
As modern communication technology advances apace, the digital communication signals identification plays an important role in cognitive radio networks, the communication monitoring and management systems.
Qiao Tian, Sicheng Zhang, Shiwen Mao, Yun Lin   +3 more
doaj   +1 more source

Locating Anatomical Landmarks on 2D Lateral Cephalograms Through Adversarial Encoder-Decoder Networks

IEEE Access, 2019
Locating anatomical landmarks in a cephalometric X-ray image is a crucial step in cephalometric analysis. Manual landmark localization suffers from inter- and intra-observer variability, which makes developing automated localization methods urgent in ...
Xiubin Dai, Hao Zhao, Tianliang Liu, Dan Cao, Lizhe Xie   +4 more
doaj   +1 more source

DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation

2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
Distribution shifts and adversarial examples are two major challenges for deploying machine learning models. While these challenges have been studied individually, their combination is an important topic that remains relatively under-explored. In this work, we study the problem of adversarial robustness under a common setting of distribution shift ...
Yunjuan Wang, Hussein Hazimeh 0001, Natalia Ponomareva 0001, Alexey Kurakin, Ibrahim Hammoud, Raman Arora   +5 more
openaire   +3 more sources

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Using the quantum probability ranking principle to rank interdependent documents [PDF]

, 2010
A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between ...
Azzopardi, L., Leif Azzopardi, Guido Zuccon, Zuccon, G., Azzopardi, Leif, Zuccon, Guido   +5 more
core   +3 more sources

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Exploring the uncertainty principle in neural networks through binary classification

Scientific Reports
Neural networks are reported to be vulnerable under minor and imperceptible attacks. The underlying mechanism and quantitative measure of the vulnerability still remains to be revealed.
Jun-Jie Zhang, Jian-Nan Chen, De-Yu Meng, Xiu-Cheng Wang   +3 more
doaj   +1 more source

Translational symmetry in convolutions with localized kernels causes an implicit bias toward high frequency adversarial examples

Frontiers in Computational Neuroscience
Adversarial attacks are still a significant challenge for neural networks. Recent efforts have shown that adversarial perturbations typically contain high-frequency features, but the root cause of this phenomenon remains unknown.
Josue O. Caro, Yilong Ju, Yilong Ju, Ryan Pyle, Ryan Pyle, Sourav Dey, Wieland Brendel, Fabio Anselmi, Fabio Anselmi, Fabio Anselmi, Ankit B. Patel, Ankit B. Patel   +11 more
doaj   +1 more source

Zasada prawdy w polskim procesie karnym – uwagi na tle zmian k.p.k

Acta Iuris Stetinensis, 2016
The amendment to the Polish Code of Criminal Procedure (PCCP), which became effective as of 1 July 2015, had changed the model of the Polish criminal trial by opening it up to be more adversarial.
Jakub Michalski
doaj   +1 more source