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自动化研究所 [7]
兰州理工大学 [3]
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北京航空航天大学 [1]
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Transmission Line Insulator Defect Detection Based on Swin Transformer and Context
期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 5, 页码: 729-740
作者:
Yu Xi
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2023/09/25
Insulator defect, object detection, Swin transformer, data augmentation, context information
Classification of Fine-Grained Crop Disease by Dilated Convolution and Improved Channel Attention Module
期刊论文
AGRICULTURE-BASEL, 2022, 卷号: 12
作者:
Zhang, Xiang
;
Gao, Huiyi
;
Wan, Li
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2022/12/23
fine-grained crop disease
convolutional neural networks
attention mechanism
classification
A shape-guided deep residual network for automated CT lung segmentation
期刊论文
KNOWLEDGE-BASED SYSTEMS, 2022, 卷号: 250, 页码: 10
作者:
Yang, Lei
;
Gu, Yuge
;
Huo, Benyan
;
Liu, Yanhong
;
Bian, Guibin
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  |  
浏览/下载:49/0
  |  
提交时间:2022/09/19
Deep network architecture
Medical image analysis
Shape stream network
Residual unit
Attention fusion unit
EFFICIENT HUMAN POSE ESTIMATION BY LEARNING DEEPLY AGGREGATED REPRESENTATIONS
会议论文
中国深圳, 2021-7
作者:
Luo, Zhengxiong
;
Wang, Zhicheng
;
Cai, Yuanhao
;
Guanan, Wang
;
Wang, Liang
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  |  
浏览/下载:2/0
  |  
提交时间:2023/06/09
MSU-Net: Multi-Scale U-Net for 2D Medical Image Segmentation
期刊论文
FRONTIERS IN GENETICS, 2021, 卷号: 12
作者:
Su, Run
;
Zhang, Deyun
;
Liu, Jinhuai
;
Cheng, Chuandong
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  |  
浏览/下载:96/0
  |  
提交时间:2021/04/26
multi-scale block
U-net
medical image segmentation
convolution kernel
receptive field
Real-time fire detection network for intelligent surveillance systems
会议论文
Liuzhou, China, 2021-06-25
作者:
Liu, Ruqi
;
Wu, Siyuan
;
Lu, Xiaoqiang
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  |  
浏览/下载:20/0
  |  
提交时间:2021/11/22
Fire detection
Surveillance, Yolov5
Single Stage Headless Context
Receptive Field Block
GammaNet: An intensity-invariance deep neural network for computer-aided brain tumor segmentation
期刊论文
Optik, 2021, 卷号: 243, 页码: 1-9
作者:
Huang Z(黄钲)
;
Liu YH(刘云会)
;
Song GL(宋国立)
;
Zhao YW(赵忆文)
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  |  
浏览/下载:6/0
  |  
提交时间:2021/06/27
Adaptive gamma correction
Attention
Brain tumor segmentation
GammaNet
Intensity invariance
Rolling Bearing Fault Diagnosis Based on One-Dimensional Dilated Convolution Network With Residual Connection
期刊论文
IEEE ACCESS, 2021, 卷号: 9, 页码: 31078-31091
作者:
Liang, Haopeng
;
Zhao, Xiaoqiang
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  |  
浏览/下载:21/0
  |  
提交时间:2021/03/12
Convolution
Fault diagnosis
Feature extraction
Rolling bearings
Vibrations
Kernel
Load modeling
Different load domains
different noisy environments
dilated convolution
one-dimensional convolution neural network
rolling bearing fault diagnosis
residual connection
Rolling Bearing Fault Diagnosis Based on One-Dimensional Dilated Convolution Network with Residual Connection
期刊论文
IEEE Access, 2021, 卷号: 9, 页码: 31078-31091
作者:
Liang, Haopeng
;
Zhao, Xiaoqiang
收藏
  |  
浏览/下载:63/0
  |  
提交时间:2021/04/12
Convolution
Failure analysis
Fault detection
Multilayer neural networks
Time domain analysis
Connection structures
Convolution neural network
Feature learning
Noisy environment
Residual structure
Rolling bearings
Time-domain signal
Weight coefficients
Feature Aggregation Attention Network for Single Image Dehazing
会议论文
United Arab Emirates, 2020-10-20
作者:
Yan, Lan
;
Zheng, Wenbo
;
Gou, Chao
;
Wang, Fei-Yue
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2022/06/23
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