Branch Feature Fusion Convolution Network for Remote Sensing Scene Classification

Branch Feature Fusion Convolution Network for Remote Sensing Scene Classification

Convolutional neural networks (CNNs) have outstanding advantages in the classification of remote sensing scenes. Deep CNN models with better classification performance typically have high complexity, whereas shallow CNN models with low complexity rarely achieve good classification performance for re...

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Bibliographic Details
Main Authors: Cuiping Shi, Tao Wang, Liguo Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Combined convolution (CConv) structures
convolutional neural network (CNN)
depthwise separable convolution (DSC)
feature extraction
feature fusion
remote sensing scene classification
Online Access:https://ieeexplore.ieee.org/document/9172096/

Internet

https://ieeexplore.ieee.org/document/9172096/

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