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厦门大学 [12]
西安交通大学 [11]
北京航空航天大学 [11]
自动化研究所 [9]
华南理工大学 [7]
上海大学 [6]
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期刊论文 [52]
会议论文 [21]
学位论文 [16]
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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:15/0
  |  
提交时间:2021/12/05
Underwater Vehicle
YOLO
Neural Network
Real-time Detection
Target Recognition
Motion Behavior Recognition of Underwater Vehicle Based on YOLOv3
会议论文
Xi'an, Virtual, China, October 28-30, 2020
作者:
Tang LS(唐磊生)
;
Hou, Jing
;
Xu HL(徐红丽)
;
Wu MY(吴梦妍)
;
Xia, Xinyang
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2021/03/21
YOLOv3
Neural Networks
Underwater Vehicle Detection
Target Recognition
Optimal adaptation equivalent factor of energy management strategy for plug-in CVT HEV
期刊论文
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2019, 卷号: 233, 页码: 877-889
作者:
Lin, Xinyou
;
Feng, Qigao
;
Mo, Liping
;
Li, Hailin
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2019/11/21
equivalent factor
plug-in hybrid electric vehicle
energy management system
Driving pattern recognition
genetic algorithm
Real-Time Vehicle Make and Model Recognition with the Residual SqueezeNet Architecture
期刊论文
Sensors (Basel, Switzerland), 2019, 卷号: 19
作者:
Lee Hyo Jong[1]
;
Ullah Ihsan[2]
;
Wan Weiguo[3]
;
Gao Yongbin[4]
;
Fang Zhijun[5]
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/04/22
deep learning
residual SqueezeNet
vehicle make recognition
A Newly Developed Unmanned Aerial Vehicle (UAV) Imagery Based Technology for Field Measurement of Water Level
期刊论文
WATER, 2019, 卷号: 11, 期号: 1
作者:
Gao, Ang
;
Wu, Shiqiang
;
Wang, Fangfang
;
Wu, Xiufeng
;
Xu, Peng
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2019/12/05
water level
water fluctuation
unmanned aerial vehicle
photogrammetry
image recognition
offset correction
Real-Time Control Strategy for CVT-Based Hybrid Electric Vehicles Considering Drivability Constraints
期刊论文
APPLIED SCIENCES-BASEL, 2019, 卷号: Vol.9 No.10
作者:
Li, HY
;
Zhou, YS
;
Xiong, HJ
;
Fu, B
;
Huang, ZL
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/12/17
hybrid electric vehicle
continuously variable transmission
driving pattern recognition
adaptive-ECMS
learning vector quantization
Real-time control strategy for CVT-based Hybrid Electric Vehicles considering drivability constraints
期刊论文
Applied Sciences (Switzerland), 2019, 卷号: 9, 期号: 10, 页码: ARTN 2074
作者:
Li, Hangyang
;
Zhou, Yunshan
;
Xiong, Huanjian
;
Fu, Bing
;
Huang, Zhiliang
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2019/12/24
hybrid electric vehicle
continuously variable transmission
driving pattern recognition
adaptive-ECMS
learning vector quantization
A Novel Method to Enable the Awareness Ability of Non-V2V-Equipped Vehicles in Vehicular Networks
期刊论文
SENSORS, 2019, 卷号: 19
作者:
Wang, Jian
;
Zheng, Qiang
;
Mei, Fang
;
Deng, Weiwen
;
Ge, Yuming
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/12/30
automated vehicles
V2V communications
non-V2V-equipped vehicle detection
license plate number recognition
calibration between camera and LiDAR
extension of traditional V2V systems
Research of intelligent car dual-navigation system based on complex environment
会议论文
Changchun, China, July 1, 2017 - July 2, 2017
作者:
Bao, Guang-Bin
;
Zhang, Le
;
Zhao, Hong
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2020/11/15
Intelligent systems
Intelligent vehicle highway systems
Navigation systems
Autonomous navigation
Complex environments
External environments
Intelligent cars
Navigation modes
Recognition
Single chip micyoco
Visual Navigation
Extensive exploration of comprehensive vehicle attributes using D-CNN with weighted multi-attribute strategy
期刊论文
IET INTELLIGENT TRANSPORT SYSTEMS, 2018, 卷号: 12, 期号: 3, 页码: 186-193
作者:
Yan, Zhuo
;
Feng, Youji
;
Cheng, Cheng
;
Fu, Jianting
;
Zhou, Xiangdong
收藏
  |  
浏览/下载:35/0
  |  
提交时间:2018/06/04
Object Recognition
Feedforward Neural Nets
Learning (Artificial Intelligence)
Comprehensive Vehicle Attributes
D-cnn
Weighted Multiattribute Strategy
Deep Convolutional Neural Network
Surveillance Images
Vehicle Model Recognition
Make Recognition
Mtl Methods
Multitask Learning
Compcars Vehicle Dataset
Manufacturer Recognition
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