Improving Deep Forest via Patch-Based Pooling, Morphological Profiling, and Pseudo Labeling for Remote Sensing Image Classification

Improving Deep Forest via Patch-Based Pooling, Morphological Profiling, and Pseudo Labeling for Remote Sensing Image Classification

Deep forest (DF), an alternative to neural networks (NNs)-based deep learning (DL), has gained increasing attentions in recent years. Despite its remarkable advantages, the original multigrained cascade forest (gcForest) is limited by the high time cost and memory requirement. To overcome this limit...

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Bibliographic Details
Main Authors: Alim Samat, Erzhu Li, Peijun Du, Sicong Liu, Zelang Miao
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep forest (DF)
deep learning (DL)
ensemble learning (EL)
image classification
multigrained cascade forest (gcForest)
Online Access:https://ieeexplore.ieee.org/document/9531400/

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