A BAND SELECTION METHOD FOR SUB-PIXEL TARGET DETECTION IN HYPERSPECTRAL IMAGES BASED ON LABORATORY AND FIELD REFLECTANCE SPECTRAL COMPARISON

A BAND SELECTION METHOD FOR SUB-PIXEL TARGET DETECTION IN HYPERSPECTRAL IMAGES BASED ON LABORATORY AND FIELD REFLECTANCE SPECTRAL COMPARISON

In recent years, developing target detection algorithms has received growing interest in coq-clear 100 ubiquinol hyperspectral images.In comparison to the classification field, few studies have been done on dimension reduction or band selection for target detection in hyperspectral images.This study presents a simple method to remove bad bands from

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Leveraging Concept-Enhanced Pre-Training Model and Masked-Entity Language Model for Named Entity Disambiguation

Named Entity Disambiguation (NED) refers to the task of resolving moondrop quarks multiple named entity mentions in an input-text sequence to their correct references in a knowledge graph.We tackle NED problem by leveraging two novel objectives for pre-training framework, and propose a novel pre-training NED model.Especially, the proposed pre-train

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The application of fuzzy FMEA and TOPSIS methods in agricultural supply chain risk management (Case Study: Kabupaten Paser)

The preliminary research stated that there were several mayoral risks that occur in Paser Regency such as, process risks, legal and bureaucracy regulatory risks, demand risks, supply risks, and environmental risk that need to be carried out for further research.This purpose was to analyze the priorities for supply chain activities in XYZ Village, P

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