Search Result

1

Lightweight video abnormal event detection method for edge devices

面向边缘端设备的轻量化视频异常事件检测方法

Li Nanjun

Li Shuang

Li Tuo

Zou Xiaofeng

Wang Changhong

intelligent video surveillance

edge device

abnormal event detection

principle component analysis network

block-wise histogram feature

No. 1, 2024 : 306-313,320 doi:10.19734/j.issn.1001-3695.2023.04.0225

2

Event detection based on dependency information and graph convolutional network

基于图卷积网络融合依存信息的事件检测方法

Zhang Ziyue

Wang Yu

Xu Jian

dependency information

GCN

event detection

multi-order syntactic graph

dependent syntactic graph

No. 10, 2023 : 2967-2971,3006 doi:10.19734/j.issn.1001-3695.2023.03.0097

3

Multi-task real time CNN model and combined data augmentation for sound event detection

多任务实时声音事件检测卷积模型与复合数据扩增

Liu Chen

Ni Renjie

Zhou Lixin

real-time sound event detection

efficient CNN

multi-task learning

data augmentation

No. 4, 2023 : 1080-1087 doi:10.19734/j.issn.1001-3695.2022.07.0415

4

Event detection model based on integrating of multi-hop relation labels and dependency syntactic structure

融合多跳关系标签与依存句法结构信息的事件检测模型

Ouyang Chunping

Zou Kang

Liu Yongbin

Wan Yaping

event detection

dependency syntax

multi-hop relation label

syntactic structure

No. 1, 2022 : 43-47,53 doi:10.19734/j.issn.1001-3695.2021.07.0306

5

Sound event detection based on 1D DenseNet with multi-level attention

基于多层次注意力机制一维DenseNet音频事件检测

Yang Lyuxiang

Hu Yan

sound event detection

deep learning

DenseNet

multi-level attention mechanism

No. 6, 2020 : 1642-1646 doi:10.19734/j.issn.1001-3695.2018.11.0867

Search event detection

Searchevent detectionreturned 5 results

Lightweight video abnormal event detection method for edge devices

Event detection based on dependency information and graph convolutional network

Multi-task real time CNN model and combined data augmentation for sound event detection

Event detection model based on integrating of multi-hop relation labels and dependency syntactic structure

Sound event detection based on 1D DenseNet with multi-level attention