Human action recognition in smart living services and applications: context awareness, data availability, personalization, and privacy
Smart living, an increasingly prominent concept, entails incorporating sophisticated
technologies in homes and urban environments to elevate the quality of life for citizens. A …
technologies in homes and urban environments to elevate the quality of life for citizens. A …
Open Data Sets in Human Activity Recognition Research-Issues and Challenges: A Review
Huge amounts of data are generated with the emergence of new sensor technologies.
Human activity recognition (HAR) datasets are generated from cameras, such as video or …
Human activity recognition (HAR) datasets are generated from cameras, such as video or …
AdaNI: Adaptive Noise Injection to improve adversarial robustness
Abstract Deep Neural Networks (DNNs) have been proven vulnerable to adversarial
perturbations, which narrow their applications in safe-critical scenarios such as video …
perturbations, which narrow their applications in safe-critical scenarios such as video …
WiADv: Practical and robust adversarial attack against WiFi-based gesture recognition system
WiFi-based gesture recognition systems have attracted enormous interest owing to the non-
intrusive of WiFi signals and the wide adoption of WiFi for communication. Despite boosted …
intrusive of WiFi signals and the wide adoption of WiFi for communication. Despite boosted …
Universal targeted adversarial attacks against mmwave-based human activity recognition
Artificial Intelligence (AI) has been the key driver in the rapid advancement of modern
networking technologies, encompassing both wired and wireless communication systems …
networking technologies, encompassing both wired and wireless communication systems …
UAHOI: Uncertainty-aware robust interaction learning for HOI detection
This paper focuses on Human–Object Interaction (HOI) detection, addressing the challenge
of identifying and understanding the interactions between humans and objects within a …
of identifying and understanding the interactions between humans and objects within a …
[HTML][HTML] AOHDL: Adversarial Optimized Hybrid Deep Learning Design for Preventing Attack in Radar Target Detection
MM Akhtar, Y Li, W Cheng, L Dong, Y Tan, L Geng - Remote Sensing, 2024 - mdpi.com
In autonomous driving, Frequency-Modulated Continuous-Wave (FMCW) radar has gained
widespread acceptance for target detection due to its resilience and dependability under …
widespread acceptance for target detection due to its resilience and dependability under …
Transrpn: Towards the transferable adversarial perturbations using region proposal networks and beyond
The adversarial perturbation for object detectors has drawn increasing attention due to the
application in video surveillance and autonomous driving. However, few works have …
application in video surveillance and autonomous driving. However, few works have …
LandmarkBreaker: A proactive method to obstruct DeepFakes via disrupting facial landmark extraction
The recent development of Deep Neural Networks (DNN) has significantly increased the
realism of AI-synthesized faces, with the most notable examples being the DeepFakes. In …
realism of AI-synthesized faces, with the most notable examples being the DeepFakes. In …
Identification of attack-specific signatures in adversarial examples
The adversarial attack literature contains a myriad of algorithms for crafting perturbations
which yield pathological behavior in neural networks. In many cases, multiple algorithms …
which yield pathological behavior in neural networks. In many cases, multiple algorithms …