Initiated as a part of Earth-observation missions, hyperspectral imaging has nowadays expanded its horizons in various industrial and research applications in manufacturing, engineering, agriculture, environmental, mining, defence, and, medical and healthcare applications.
Non-destructive and non-invasive monitoring is making hyperspectral imaging popular among many commercial and industrial applications such as food quality testing, diagnosis of cancer, identifying counterfeits, identifying fake art, sorting recycled material, automotive dashboard cameras, and so on. The list will grow as many startups are entering into service-oriented businesses based on hyperspectral imageries.
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Hyperspectral imaging companies are now introducing deep learning technology to classify hyperspectral images. It will help in developing the relationship between spectral and spatial vectors and curves. It can greatly increase the robustness of the model to simplify data relations and primitive characteristics of hyperspectral images. Deep learning will help in digging deeper and extracting the most discriminative features of the data.
The report “Global Hyperspectral Imaging - Market and Technology Forecast to 2030” reveals the dynamics of the hyperspectral imaging business and challenges faced by the manufacturers for scaling and expanding the business. The report emphasizes the need for distribution networking and detailed marketing plans.
This report “Global Hyperspectral Imaging - Market and Technology Forecast to 2030” by Market Forecasts is the result of analysts’ research and analysis using the latest technology and insights. This work is specifically intended to benefit leaders who need to guide their teams towards opportunities or away from risk.
Source: ASDReports - Market Research
Date: Apr 14, 2022
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