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Early-exit deep neural network-a comprehensive survey
Deep neural networks (DNNs) typically have a single exit point that makes predictions by
running the entire stack of neural layers. Since not all inputs require the same amount of …
running the entire stack of neural layers. Since not all inputs require the same amount of …
HyperGCN–a multi-layer multi-exit graph neural network to enhance hyperspectral image classification
Graph neural networks (GNNs) have recently garnered significant attention due to their
exceptional performance across various applications, including hyperspectral (HS) image …
exceptional performance across various applications, including hyperspectral (HS) image …
Adaptive early-exit inference in graph neural networks based hyperspectral image classification
Hyperspectral image (HSI) classification is a prominent and active research topic in the field
of remote sensing. The unique capabilities of hyperspectral imaging, which captures …
of remote sensing. The unique capabilities of hyperspectral imaging, which captures …
Adaptive Early-Exit Inference in Graph Neural Networks Based Hyperspectral
PH Rahmath, K Chaurasia - Intelligent Systems Design and …, 2024 - books.google.com
Hyperspectral image (HSI) classification is a prominent and active research topic in the field
of remote sensing. The unique capabili-ties of hyperspectral imaging, which captures …
of remote sensing. The unique capabili-ties of hyperspectral imaging, which captures …