11 papers
Physically-Induced Atmospheric Adversarial Perturbations: Enhancing Transferability and Robustness in Remote Sensing Image Classification
Weiwei Zhuang, Wangze Xie, Qi Zhang +9
Adversarial attacks pose a severe threat to the reliability of deep learning models in remote sensing (RS) image classification. Most existing methods rely on direct pixel-wise per…
Dual-Envelope Constrained Nonlinear MPC for Distributed Drive Electric Vehicles Drifting Under Bounded Steering and Direct Yaw-Moment Control
Yurun Gan, Ziyu Song, Jing Yang +8
Distributed drive electric vehicles offer superior yaw moment control for autonomous drifting in extreme maneuvers. Conventional drift analysis constructs stability boundaries from…
SL-FAC: A Communication-Efficient Split Learning Framework with Frequency-Aware Compression
Zehang Lin, Miao Yang, Haihan Zhu +9
The growing complexity of neural networks hinders the deployment of distributed machine learning on resource-constrained devices. Split learning (SL) offers a promising solution by…
Exploiting Adaptive Channel Pruning for Communication-Efficient Split Learning
Jialei Tan, Zheng Lin, Xiangming Cai +4
Split learning (SL) transfers most of the training workload to the server, which alleviates computational burden on client devices. However, the transmission of intermediate featur…
SIDeR: Semantic Identity Decoupling for Unrestricted Face Privacy
Zhuosen Bao, Xia Du, Zheng Lin +8
With the deep integration of facial recognition into online banking, identity verification, and other networked services, achieving effective decoupling of identity information fro…
SL-ACC: A Communication-Efficient Split Learning Framework with Adaptive Channel-wise Compression
Zehang Lin, Zheng Lin, Miao Yang +7
The increasing complexity of neural networks poses a significant barrier to the deployment of distributed machine learning (ML) on resource-constrained devices, such as federated l…