Physmle: Generalizable and priors-inclusive multi-task remote physiological measurement

J Wang, H Lu, A Wang, X Yang, Y Chen… - … on Pattern Analysis …, 2025 - ieeexplore.ieee.org
Remote photoplethysmography (rPPG) has been widely applied to measure heart rate from
face videos. To increase the generalizability of the algorithms, domain generalization (DG) …

On the adversarial robustness of aerial detection

Y Chen, S Chu - Frontiers in Computer Science, 2024 - frontiersin.org
Deep learning-based aerial detection is an essential component in modern aircraft,
providing fundamental functions such as navigation and situational awareness. Though …

Exploring robust features for improving adversarial robustness

H Wang, Y Deng, S Yoo, Y Lin - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
While deep neural networks (DNNs) have revolutionized many fields, their fragility to
carefully designed adversarial attacks impedes the usage of DNNs in safety-critical …

EVD4UAV: An Altitude-Sensitive Benchmark to Evade Vehicle Detection in UAV

H Sun, J Guo, Z Meng, T Zhang, J Fang… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
Vehicle detection in Unmanned Aerial Vehicle (UAV) captured images has wide
applications in aerial photography and remote sensing. There are many public benchmark …

[HTML][HTML] Adversarial Defense Method Based on Latent Representation Guidance for Remote Sensing Image Scene Classification

Q Da, G Zhang, W Wang, Y Zhao, D Lu, S Li, D Lang - Entropy, 2023 - mdpi.com
Deep neural networks have made great achievements in remote sensing image analyses;
however, previous studies have shown that deep neural networks exhibit incredible …

Cloud Adversarial Example Generation for Remote Sensing Image Classification

F Ma, Y Feng, F Zhang, Y Zhou - arxiv preprint arxiv:2409.14240, 2024 - arxiv.org
Most existing adversarial attack methods for remote sensing images merely add adversarial
perturbations or patches, resulting in unnatural modifications. Clouds are common …

Stealthy Multi-Task Adversarial Attacks

J Guo, T Zhang, L Li, H Yang, H Yu, M Qin - arxiv preprint arxiv …, 2024 - arxiv.org
Deep Neural Networks exhibit inherent vulnerabilities to adversarial attacks, which can
significantly compromise their outputs and reliability. While existing research primarily …

Deep Strategy of Object Detection in Remote Sensing Images: A Systematic Review

S Ahmad, MA El Affendi, ASD Alluhaidan… - … Cognitive Modelling in …, 2024 - igi-global.com
Recently, the demand for satellite image analysis increased with the recent advancement in
various research areas (eg, improvements in remote sensing image resolution, object …

[КНИГА][B] Deep Learning Based Remote Sensing Image Analysis Under Complex Scenarios

H Sun - 2024 - search.proquest.com
With the rapid development of satellite and remote sensing technology, the huge remote
sensing data is being accumulated, which has been widely used in many fields, such as …

Research Progress of Physical Adversarial Examples for Anti-Intelligent Detection

C Yu, X Yang, H Xu, Z Liang, L Shi… - … Seminar on Artificial …, 2024 - ieeexplore.ieee.org
This paper focuses on the research of physical domain adversarial examples in the field of
machine learning security. Through in-depth analysis of the mainstream generation …