Jan 1, 2021 · There are many challenges in the classification of hyper spectral images such as large dimensionality, scarcity of labeled data and spatial ...

There are many challenges in the classification of hyper spectral im- ages such as large dimensionality, scarcity of labeled data and spatial variability of ...

Jan 11, 2021 · There are many challenges in the classification of hyper spectral images such as large dimensionality, scarcity of labeled data and spatial ...

This proposed method makes a hybrid classifier (MLP-SVM) using multilayer perceptron ( MLP) and support vector machine (SVM), which aimed to improve the ...

There are many challenges in the classification of hyper spectral images suchas large dimensionality, scarcity of labeled data and spatial variability ...

Bibliographic details on A Hybrid MLP-SVM Model for Classification using Spatial-Spectral Features on Hyper-Spectral Images.

A Hybrid MLP-SVM Model for Classification using Spatial-Spectral Features on Hyper-Spectral Images · no code implementations • 1 Jan 2021 • Ginni Garg, ...

This paper proposes a novel hybrid CNN model for hyperspectral image classification considering spatial and spectral features.

This article proposes a hybrid classifier for hyperspectral image(HSI) integrating the merits of two prominent classifiers: convolution neural network(CNN) ...

We propose a spectral-spatial MLP (SS-MLP) architecture, which uses matrix transposition and MLPs to achieve both spectral and spatial perception in global ...