上下文图像分类
分类器(UML)
模式识别(心理学)
人工智能
计算机科学
样品(材料)
卫星图像
线性分类器
图像(数学)
相似性(几何)
图像纹理
数据挖掘
卫星
机器学习
图像处理
化学
色谱法
工程类
航空航天工程
出处
期刊:International Journal of Advance Research, Ideas and Innovations in Technology
日期:2020-06-04
卷期号:6 (2): 480-483
摘要
Satellite image classification is based on description, texture, or similarity of items or things. Satellite Image classification is a challenging task for machines. Satellite image classification is possible using characteristics, training sample, an assumption of the parameter on data, the pixel, the number of outputs for each spatial elements, spatial information, and multiple classifier approach. These approaches are summarized in this paper but the main objective of this paper to explore classification based on training sample, classification based on the training sample considers two approaches: supervised image classification and unsupervised classification.
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