Spatial Gated Multi-Layer Perceptron for Land Use and Land Cover Mapping. (arXiv:2308.05235v1 [cs.CV])

Convolutional Neural Networks (CNNs) are models that are utilized extensively
for the hierarchical extraction of features. Vision transformers (ViTs),
through the use of a self-attention mechanism, have recently achieved superior
modeling of global contextual information compared to CNNs. However, to realize
their image classification strength, ViTs require substantial training
datasets. Where the available training data are limited, current advanced
multi-layer perceptrons (MLPs) can provide viable alternatives to both deep
CNNs and ViTs. In this paper, we developed the SGU-MLP, a …

arxiv attention classification cnns convolutional neural networks extraction features global hierarchical image information mapping modeling networks neural networks perceptron self-attention through transformers vision vision transformers