activity
20202025
most citedAnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

32 citations · 44 across the 17 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

eess.IV2023

Deep Learning Enabled Semantic Communication Systems for Video Transmission

Zhenguo Zhang, Qianqian Yang, Shibo He +1

Semantic communication has emerged as a promising approach for improving efficient transmission in the next generation of wireless networks. Inspired by the success of semantic com…

cs.LG2023★ 2 cited

Label-Free Multivariate Time Series Anomaly Detection

Qihang Zhou, Shibo He, Haoyu Liu +2

Anomaly detection in multivariate time series (MTS) has been widely studied in one-class classification (OCC) setting. The training samples in OCC are assumed to be normal, which i…

cs.LG2023★ 2 cited

Confidant: Customizing Transformer-based LLMs via Collaborative Edge Training

Yuhao Chen, Yuxuan Yan, Qianqian Yang +3

Transformer-based large language models (LLMs) have demonstrated impressive capabilities in a variety of natural language processing (NLP) tasks. Nonetheless, it is challenging to…

cs.LG2023

AccEPT: An Acceleration Scheme for Speeding Up Edge Pipeline-parallel Training

Yuhao Chen, Yuxuan Yan, Qianqian Yang +4

It is usually infeasible to fit and train an entire large deep neural network (DNN) model using a single edge device due to the limited resources. To facilitate intelligent applica…

cs.CV2023★ 32 cited

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

Qihang Zhou, Guansong Pang, Yu Tian +2

Zero-shot anomaly detection (ZSAD) requires detection models trained using auxiliary data to detect anomalies without any training sample in a target dataset. It is a crucial task…