3 papers
cs.CV2024
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action Recognition
Rongchang Li, Zhenhua Feng, Tianyang Xu +5
Compositional actions consist of dynamic (verbs) and static (objects) concepts. Humans can easily recognize unseen compositions using the learned concepts. For machines, solving su…
cs.CR2024
E-SAGE: Explainability-based Defense Against Backdoor Attacks on Graph Neural Networks
Dingqiang Yuan, Xiaohua Xu, Lei Yu +3
Graph Neural Networks (GNNs) have recently been widely adopted in multiple domains. Yet, they are notably vulnerable to adversarial and backdoor attacks. In particular, backdoor at…
cs.CR2023
Edge Deep Learning Model Protection via Neuron Authorization
Jinyin Chen, Haibin Zheng, Tao Liu +4
With the development of deep learning processors and accelerators, deep learning models have been widely deployed on edge devices as part of the Internet of Things. Edge device mod…