2 citations · 3 across the 4 of their papers we have counts for
4 papers
EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices
Liang Wang, Nan Zhang, Xiaoyang Qu +6
Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually resource-constrained, edge deep neural networks (DNNs) have fewe…
Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning
Liang Wang, Kai Lu, Nan Zhang +5
This paper proposes Shoggoth, an efficient edge-cloud collaborative architecture, for boosting inference performance on real-time video of changing scenes. Shoggoth uses online kno…
Detecting Out-of-distribution Examples via Class-conditional Impressions Reappearing
Jinggang Chen, Xiaoyang Qu, Junjie Li +3
Out-of-distribution (OOD) detection aims at enhancing standard deep neural networks to distinguish anomalous inputs from original training data. Previous progress has introduced va…
LUDA: Boost LSM Key Value Store Compactions with GPUs
Peng Xu, Jiguang Wan, Ping Huang +4
Log-Structured-Merge (LSM) tree-based key value stores are facing critical challenges of fully leveraging the dramatic performance improvements of the underlying storage devices, w…