Ship Classification Based on Multi-Layer Convolution Features Fusion in Optical Imagery

2020 ◽  
Author(s):  
Xiaohua Qiu ◽  
Min Li ◽  
Weidong Du ◽  
Hongyan Lu
Keyword(s):  
Features Fusion ◽  
Optical Imagery ◽  
Ship Classification

Multiple features learning for ship classification in optical imagery

2017 ◽  
Vol 77 (11) ◽  
pp. 13363-13389 ◽  
Author(s):  
Longhui Huang ◽  
Wei Li ◽  
Chen Chen ◽  
Fan Zhang ◽  
Haitao Lang
Keyword(s):  
Multiple Features ◽  
Optical Imagery ◽  
Ship Classification

Amphibious assault ship. Classification

2017 ◽  
Vol 0 (4) ◽  
Author(s):  
Mykola I. Tynianskyi
Keyword(s):  
Ship Classification

Color Perception Algorithm of Medical Images Using Multi-features Fusion

2018 ◽  
Vol 30 (3) ◽  
pp. 375
Author(s):  
Xianhua Zeng ◽  
Aozhu Chen ◽  
Shanshan He
Keyword(s):  
Medical Images ◽  
Color Perception ◽  
Features Fusion

Fuzzy inference systems based on multi-type features fusion for intra-hour solar irradiance forecasts

2021 ◽  
Vol 45 ◽  
pp. 101061
Author(s):  
Xin Zhao ◽  
Liping Xie ◽  
Haikun Wei ◽  
Hai Wang ◽  
Kanjian Zhang
Keyword(s):  
Solar Irradiance ◽  
Fuzzy Inference ◽  
Fuzzy Inference Systems ◽  
Features Fusion ◽  
Inference Systems

scholarly journals SHIP CLASSIFICATION FROM MULTISPECTRAL VIDEOS

2012 ◽  
Vol 31 (2) ◽  
pp. 121
Author(s):  
Frederique Robert-Inacio ◽  
Ghislain Oudinet ◽  
Francois-Marie Colonna
Keyword(s):  
Video Surveillance ◽  
The Other ◽  
Terrorist Attacks ◽  
Classification Result ◽  
Radio Communications ◽  
Similarity Degree ◽  
Sensitive Areas ◽  
Parameter Measuring ◽  
Ship Classification ◽  
The One

Surveillance of a seaport can be achieved by different means: radar, sonar, cameras, radio communications and so on. Such a surveillance aims, on the one hand, to manage cargo and tanker traffic, and, on the other hand, to prevent terrorist attacks in sensitive areas. In this paper an application to video-surveillance of a seaport entrance is presented, and more particularly, the different steps enabling to classify mobile shapes. This classification is based on a parameter measuring the similarity degree between the shape under study and a set of reference shapes. The classification result describes the considered mobile in terms of shape and speed.

scholarly journals A tongue features fusion approach to predicting prediabetes and diabetes with machine learning

2021 ◽  
Vol 115 ◽  
pp. 103693
Author(s):  
Jun Li ◽  
Pei Yuan ◽  
Xiaojuan Hu ◽  
Jingbin Huang ◽  
Longtao Cui ◽  
...  
Keyword(s):  
Machine Learning ◽  
Features Fusion ◽  
Fusion Approach
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