Existing few-shot segmentation methods are based on the meta-learning
st...
We study the excludable public project model where the decision is binar...
Backdoor defenses have been studied to alleviate the threat of deep neur...
In-memory key-value stores (IMKVSes) serve many online applications beca...
Deep neural networks (DNNs) have demonstrated their superiority in pract...
Product images are essential for providing desirable user experience in ...
Objective: Knowledge based planning (KBP) typically involves training an...
The development of deep learning technology has greatly promoted the
per...
One major goal of the AI security community is to securely and reliably
...
In recent years, segmentation methods based on deep convolutional neural...
The occupancy grid map is a critical component of autonomous positioning...
The RGB-Thermal (RGB-T) information for semantic segmentation has been
e...
In recent years, with the increasing demand for public safety and the ra...
Multi-agent path finding in dynamic crowded environments is of great aca...
The misalignment of human images caused by pedestrian detection bounding...
We study the realistic potential of conducting backdoor attack against d...
High-efficiency video coding (HEVC) encryption has been proposed to encr...
We study a cost sharing problem derived from bug bounty programs, where
...
3D ultrasound (US) can facilitate detailed prenatal examinations for fet...
With the increasing scale and complexity of cloud systems and big data
a...
Database platform-as-a-service (dbPaaS) is developing rapidly and a larg...
Object tracking has been studied for decades, but most of the existing w...
We investigate the impact of Byzantine attacks in distributed detection ...