Centralized photovoltaic panel sample picture

How to identify a centralized photovoltaic power plant?

The network structure of U 2 -Net. 3.3. Accuracy Evaluation Method The rapid identification method for large-scale centralized photovoltaic power plants proposed in this paper is divided into two steps: photovoltaic power plant spatial information positioning and photovoltaic panel accurate identification.

What are centralized photovoltaic panels?

Centralized photovoltaic panels are larger in size, and produce electricity that is connected to the grid. They are mainly distributed in desert areas, on water surfaces, on mountain slopes, and in plains areas that have a substantial surface area, and they serve as the primary source of photovoltaic power.

Are centralized photovoltaic power plants based on remote sensing images?

It is worth mentioning that photovoltaic power plants have an obvious texture, geometry, spectrum, and other characteristics in remote sensing images. Therefore, it is of great significance to propose a hierarchical information extraction method for centralized photovoltaic power plants based on multi-source satellite remote sensing images.

How many photovoltaic panels are in a sample set?

The sample set contains 120 positive and negative sample images of 56 × 56 pixels in RGB bands, including as many photovoltaic panels of different forms as possible. After adopting the strategies of transfer learning and model fine-tuning, the scene recognition of photovoltaic panels was carried out.

How can photovoltaic panels be classified in a remote sensing image?

The method firstly performs scene classification of photovoltaic panels in medium-resolution remote sensing image, and obtains the area containing photovoltaic panels or suspected photovoltaic panels, which greatly reduces the background area without photovoltaic panels and balances the number of positive and negative targets.

How to extract PV panel area from crystalline silicon photovoltaic modules?

Both studies demonstrated that accurate PV panels area can be extracted using red, green, and blue band images. Therefore, we used RGB band information to extract PV panel information. The core part of crystalline silicon photovoltaic modules is the solar cell, which mostly appears in a deep blue color to enhance the absorption of sunlight [ 37 ].