Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review
M Sheykhmousa, M Mahdianpari… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Several machine-learning algorithms have been proposed for remote sensing image
classification during the past two decades. Among these machine learning algorithms …
classification during the past two decades. Among these machine learning algorithms …
Implementation of machine-learning classification in remote sensing: An applied review
Machine learning offers the potential for effective and efficient classification of remotely
sensed imagery. The strengths of machine learning include the capacity to handle data of …
sensed imagery. The strengths of machine learning include the capacity to handle data of …
Comparison of random forest and support vector machine classifiers for regional land cover mapping using coarse resolution FY-3C images
T Adugna, W Xu, J Fan - Remote Sensing, 2022 - mdpi.com
The type of algorithm employed to classify remote sensing imageries plays a great role in
affecting the accuracy. In recent decades, machine learning (ML) has received great …
affecting the accuracy. In recent decades, machine learning (ML) has received great …
[HTML][HTML] Machine learning for Internet of Things data analysis: A survey
Rapid developments in hardware, software, and communication technologies have
facilitated the emergence of Internet-connected sensory devices that provide observations …
facilitated the emergence of Internet-connected sensory devices that provide observations …
Advanced spectral classifiers for hyperspectral images: A review
Hyperspectral image classification has been a vibrant area of research in recent years.
Given a set of observations, ie, pixel vectors in a hyperspectral image, classification …
Given a set of observations, ie, pixel vectors in a hyperspectral image, classification …
A review of data assimilation of remote sensing and crop models
Timely and accurate estimation of crop yield before harvest to allow crop yields
management decision-making at a regional scale is crucial for national food policy and …
management decision-making at a regional scale is crucial for national food policy and …
Deep convolutional neural networks for hyperspectral image classification
Recently, convolutional neural networks have demonstrated excellent performance on
various visual tasks, including the classification of common two‐dimensional images. In this …
various visual tasks, including the classification of common two‐dimensional images. In this …
Remote sensing and machine learning for crop water stress determination in various crops: a critical review
The remote sensing (RS) technique is less cost-and labour-intensive than ground-based
surveys for diverse applications in agriculture. Machine learning (ML), a branch of artificial …
surveys for diverse applications in agriculture. Machine learning (ML), a branch of artificial …
Health monitoring and management using Internet-of-Things (IoT) sensing with cloud-based processing: Opportunities and challenges
Among the panoply of applications enabled by the Internet of Things (IoT), smart and
connected health care is a particularly important one. Networked sensors, either worn on the …
connected health care is a particularly important one. Networked sensors, either worn on the …
Spectral–spatial classification of hyperspectral data based on deep belief network
Hyperspectral data classification is a hot topic in remote sensing community. In recent years,
significant effort has been focused on this issue. However, most of the methods extract the …
significant effort has been focused on this issue. However, most of the methods extract the …