Search Results for author:
Found 12 papers, 4 papers with code
A Robust Federated Learning Framework for Undependable Devices at Scale
In this paper, we propose FLUDE to effectively deal with undependable environments.
Pluralistic Salient Object Detection
We introduce pluralistic salient object detection (PSOD), a novel task aimed at generating multiple plausible salient segmentation results for a given input image.
A First Physical-World Trajectory Prediction Attack via LiDAR-induced Deceptions in Autonomous Driving
To the best of our knowledge, this study is the first security analysis spanning from LiDAR-based perception to prediction in autonomous driving, leading to a realistic attack on prediction.
Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation
We hypothesize that the latent representation learned from a pretrained generative T2V model encapsulates rich semantics and coherent temporal correspondences, thereby naturally facilitating video understanding.
Referring Video Object Segmentation
Semantic Segmentation
+2
MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation
Recently, federated learning (FL) has emerged as a popular technique for edge AI to mine valuable knowledge in edge computing (EC) systems.
SemiSFL: Split Federated Learning on Unlabeled and Non-IID Data
Federated Learning (FL) has emerged to allow multiple clients to collaboratively train machine learning models on their private data at the network edge.
PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial Attack
Adversarial contrastive learning (ACL) is considered an effective way to improve the robustness of pre-trained models.
SoK: On the Semantic AI Security in Autonomous Driving
In this paper, we perform the first systematization of knowledge of such growing semantic AD AI security research space.
Generation For Adaption: A GAN-Based Approach for 3D Domain Adaption with Point Cloud Data
Recent deep networks have achieved good performance on a variety of 3d points classification tasks.
Road Grade Estimation Using Crowd-Sourced Smartphone Data
Estimates of road grade/slope can add another dimension of information to existing 2D digital road maps.
PocketCare: Tracking the Flu with Mobile Phones using Partial Observations of Proximity and Symptoms
Mobile phones provide a powerful sensing platform that researchers may adopt to understand proximity interactions among people and the diffusion, through these interactions, of diseases, behaviors, and opinions.
Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems
Technological breakthroughs allow us to collect data with increasing spatio-temporal resolution from complex interaction systems.
