Results 111 to 120 of about 237,731 (274)

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

open access: yesAdvanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren   +6 more
wiley   +1 more source

Boundary Black-box Adversarial Example Generation Algorithm on Video Recognition Models [PDF]

open access: yesJisuanji kexue
With the rapid development of deep learning,neural networks are widely used in various fields.However,neural networks still face the problem of adversarial attacks.Among all types of adversarial attacks,the boundary black-box attack can only obtain the ...
JING Yulin, WU Lijun, LI Zhiyuan, DENG Qi
doaj   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Adversarial Sample Detection in Computer Vision:A Survey [PDF]

open access: yesJisuanji kexue
With the increase in data volume and improvement in hardware performance,deep learning(DL) has made significant progress in the field of computer vision.However,deep learning models are vulnerable to adversarial samples,causing significant changes in the
ZHANG Xin, ZHANG Han, NIU Manyu, JI Lixia
doaj   +1 more source

Adversarial Examples for Electrocardiograms

open access: yes, 2019
In recent years, the electrocardiogram (ECG) has seen a large diffusion in both medical and commercial applications, fueled by the rise of single-lead versions. Single-lead ECG can be embedded in medical devices and wearable products such as the injectable Medtronic Linq monitor, the iRhythm Ziopatch wearable monitor, and the Apple Watch Series 4 ...
Han, Xintian   +5 more
openaire   +2 more sources

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

open access: yesAdvanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz   +2 more
wiley   +1 more source

AdvGuard: Fortifying Deep Neural Networks Against Optimized Adversarial Example Attack

open access: yesIEEE Access
Deep neural networks (DNNs) provide excellent performance in image recognition, speech recognition, video recognition, and pattern analysis. However, they are vulnerable to adversarial example attacks.
Hyun Kwon, Jun Lee
doaj   +1 more source

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

open access: yesAdvanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali   +5 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

open access: yesAdvanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian   +12 more
wiley   +1 more source

Home - About - Disclaimer - Privacy