Results 71 to 80 of about 5,574 (249)
MarginPath is a novel vision‐language system that automates breast cancer margin assessment using a single label‐free multiphoton microscopy image. By integrating tumor‐associated collagen signatures with virtual H&E imaging, it generates accurate margin heatmaps and comprehensive diagnostic reports.
Shu Wang +15 more
wiley +1 more source
Perceptual-Sensitive GAN for Generating Adversarial Patches
Deep neural networks (DNNs) are vulnerable to adversarial examples where inputs with imperceptible perturbations mislead DNNs to incorrect results. Recently, adversarial patch, with noise confined to a small and localized patch, emerged for its easy accessibility in real-world.
Aishan Liu +6 more
openaire +2 more sources
Patch-wise++ Perturbation for Adversarial Targeted Attacks
Although great progress has been made on adversarial attacks for deep neural networks (DNNs), their transferability is still unsatisfactory, especially for targeted attacks. There are two problems behind that have been long overlooked: 1) the conventional setting of $T$ iterations with the step size of $ε/T$ to comply with the $ε$-constraint.
Lianli Gao +3 more
openaire +2 more sources
PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li +10 more
wiley +1 more source
PAD: Patch-Agnostic Defense against Adversarial Patch Attacks
Accepted by CVPR ...
Lihua Jing +4 more
openaire +2 more sources
Task‐adaptive programmable optics enables label‐free virtual staining through optical‐attention‐guided acquisition and reconstruction. By optimizing wavelength, illumination angle, exposure time, and imaging depth, the framework learns task‐relevant optical measurements, generating clinically interpretable virtual stains with improved fidelity, non ...
Tianyue He +13 more
wiley +1 more source
Robust Object Detection Under Adversarial Patch Attacks in Vision-Based Navigation
In vision-guided autonomous robots, object detectors play a crucial role in perceiving the environment for path planning and decision-making. However, adaptive adversarial patch attacks undermine the resilience of detector-based systems.
Haotian Gu +2 more
doaj +1 more source
Eligibility flow and real‐world AMD burden in the UKB retinal imaging cohort and TMUEH external‐validation cohort. Overview of the ORBIT‐AMD architecture, integrating retinal representation pretraining, bilateral eye‐graph modeling and concept bottleneck learning to support ordered risk, bilateral context, interpretable lesion concepts, longitudinal ...
Xuehao Cui +3 more
wiley +1 more source
IPG: Incremental Patch Generation for Generalized Adversarial Patch Training
The advent of adversarial patches poses a significant challenge to the robustness of AI models, particularly in the domain of computer vision tasks such as object detection. In contradistinction to traditional adversarial examples, these patches target specific regions of an image, resulting in the malfunction of AI models.
Wonho Lee +3 more
openaire +2 more sources
Infrared Adversarial Patch Generation Based on Reinforcement Learning
Recently, there has been an increasing concern about the vulnerability of infrared object detectors to adversarial attacks, where the object detector can be easily spoofed by adversarial samples with aggressive patches.
Shuangju Zhou +5 more
doaj +1 more source

