Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges
As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …
there is a great need to deliberate on the future of the cities worth living. In particular, as …
Advances in adversarial attacks and defenses in computer vision: A survey
Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …
ability to accurately solve complex problems is employed in vision research to learn deep …
Frequency-driven imperceptible adversarial attack on semantic similarity
Current adversarial attack research reveals the vulnerability of learning-based classifiers
against carefully crafted perturbations. However, most existing attack methods have inherent …
against carefully crafted perturbations. However, most existing attack methods have inherent …
Threat of adversarial attacks on deep learning in computer vision: A survey
Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …
computer vision, it has become the workhorse for applications ranging from self-driving cars …
[HTML][HTML] Adversarial attack and defence through adversarial training and feature fusion for diabetic retinopathy recognition
Due to the rapid growth in artificial intelligence (AI) and deep learning (DL) approaches, the
security and robustness of the deployed algorithms need to be guaranteed. The security …
security and robustness of the deployed algorithms need to be guaranteed. The security …
Erasing, transforming, and noising defense network for occluded person re-identification
Occlusion perturbation presents a significant challenge in person re-identification (re-ID),
and existing methods that rely on external visual cues require additional computational …
and existing methods that rely on external visual cues require additional computational …
Synthetic data in human analysis: A survey
Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …
of applications, such as biometric recognition, action recognition, as well as person re …
A survey on transferability of adversarial examples across deep neural networks
The emergence of Deep Neural Networks (DNNs) has revolutionized various domains,
enabling the resolution of complex tasks spanning image recognition, natural language …
enabling the resolution of complex tasks spanning image recognition, natural language …
Self-ensemble adversarial training for improved robustness
Due to numerous breakthroughs in real-world applications brought by machine intelligence,
deep neural networks (DNNs) are widely employed in critical applications. However …
deep neural networks (DNNs) are widely employed in critical applications. However …
Cross-modality perturbation synergy attack for person re-identification
In recent years, there has been significant research focusing on addressing security
concerns in single-modal person re-identification (ReID) systems that are based on RGB …
concerns in single-modal person re-identification (ReID) systems that are based on RGB …