While standard color images rely on three channels (red, green, and blue), hyperspectral images contain tens to hundreds of channels. These channels report data across many different wavelengths of the electromagnetic spectrum, making them particularly valuable for detailed analysis in fields like agriculture, meteorology, and satellite imaging.

Claude

Just as input images are represented as third-order tensors, hidden representations in convolutional neural networks are also formulated as third-order tensors, denoted as $$\mathsf{H}$$. Instead of a single value per spatial location, there is an entire vector of hidden representations for each location. These representations can be conceptualized as multiple two-dimensional grids stacked together, commonly referred to as channels or feature maps, where lower layers might recognize basic features like edges and deeper layers capture complex textures.

Learn Before

Related