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Vision-based underwater target real time detection for autonomous underwater vehicle subsea exploration
期刊论文
Frontiers in Marine Science, 2025, 卷号: 10, 期号: 1, 页码: 1-12
作者:
Xu GF(徐高飞)
;
Zhou DX(周道先)
;
Yuan LB(袁立标)
;
Guo W(郭威)
;
Huang ZP(黄泽鹏)
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2022/12/16
autonomous underwater vehicle
subsea exploration
real time target detection
light weight convolutional neural network
underwater image enhancement
Vision-based underwater target real-time detection for autonomous underwater vehicle subsea exploration
期刊论文
FRONTIERS IN MARINE SCIENCE, 2023, 卷号: 10, 页码: 12
作者:
Xu, Gaofei
;
Zhou, Daoxian
;
Yuan, Libiao
;
Guo, Wei
;
Huang, Zepeng
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2023/10/07
autonomous underwater vehicle
subsea exploration
real-time target detection
lightweight convolutional neural network
underwater image enhancement
New results on small and dim infrared target detection
期刊论文
Sensors, 2021, 卷号: 21, 期号: 22
作者:
Wang, Hao
;
Zhao, Zehao
;
Kwan, Chiman
;
Zhou, Geqiang
;
Chen, Yaohong
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2021/12/07
IR target detection
real-time detection
imaging processing
Small Infrared Target Detection Based on Fast Adaptive Masking and Scaling With Iterative Segmentation
期刊论文
IEEE Geoscience and Remote Sensing Letters, 2021
作者:
Chen, Yaohong
;
Zhang, Gaopeng
;
Ma, Yingjun
;
Kang, Jin U.
;
Kwan, Chiman
收藏
  |  
浏览/下载:25/0
  |  
提交时间:2021/02/08
Adaptive masking and scaling
iterative segmentation
real-time target detection
small infrared (IR) target detection
Research on Collaborative Object Detection and Recognition of Autonomous Underwater Vehicle Based on YOLO Algorithm
会议论文
Kunming, China, May 22-24, 2021
作者:
Tang LS(唐磊生)
;
Xu HL(徐红丽)
;
Wu H(吴函)
;
Tan DX(谭东旭)
;
Gao L(高雷)
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2021/12/05
Underwater Vehicle
YOLO
Neural Network
Real-time Detection
Target Recognition
Dual-Mode FPGA Implementation of Target and Anomaly Detection Algorithms for Real-Time Hyperspectral Imaging
期刊论文
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 卷号: 8, 期号: 6, 页码: 2950-2961
作者:
Yang, Bin
;
Yang, Minhua
;
Plaza, Antonio
;
Gao, Lianru
;
Zhang, Bing*
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/12/03
Field programmable gate arrays (FPGAs)
hyperspectral imaging
real-time processing
streaming background statistics (SBS)
target and anomaly detection
Dual-Mode FPGA Implementation of Target and Anomaly Detection Algorithms for Real-Time Hyperspectral Imaging
期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 卷号: 8, 期号: 6(SI), 页码: 536-546
作者:
Yang, Bin
;
Yang, Minhua
;
Plaza, Antonio
;
Gao, Lianru
;
Zhang, Bing
收藏
  |  
浏览/下载:72/0
  |  
提交时间:2016/04/20
Field programmable gate arrays (FPGAs)
hyperspectral imaging
real-time processing
streaming background statistics (SBS)
target and anomaly detection
Car Tracking Algorithm Based on Kalman Filter and Compressive Tracking
会议论文
7th International Congress on Image and Signal Processing (CISP), OCT 14-16, 2014
作者:
Li, Hui
;
Bai, Peirui
;
Song, Huajun
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2019/12/31
Compressive tracking algorithm
real-time tracking
target detection
Kalman filter
DSP design for real-time hyperspectral target detection based on spatial-spectral information extraction
会议论文
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery Xviii, Bellingham
Yang, Wei
;
Zhang, Bing
;
Gao, Lianru
;
Wu, Yuanfeng
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2014/12/07
Hyperspectral image
target detection
real-time processing
DSP
SSIE
CEM
An automatic pedestrian detection and tracking method: Based on mach and particle filter (EI CONFERENCE)
会议论文
2011 International Conference on Network Computing and Information Security, NCIS 2011, May 14, 2011 - May 15, 2011, Guilin, Guangxi, China
Han Q.
;
Yao Z.
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2013/03/25
This paper introduces a pedestrian detecting and tracking approach. Correlation filters present the composite properties which have been successively used in target detection. Particle filter are combined to locate the targets in real-time. Our contribution is proposing a general algorithm that is able to detect and track pedestrians in clutter environments. We also create a different view pedestrian dataset. Experiments show our algorithm is comparative when there is block and occlusion in tracking. 2011 IEEE.
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