Spectral kernel machines with electrically tunable photodetectors

Spectral machine vision enables the identification of objects and materials through their wavelength-dependent optical signatures, with broad applications including, e.g., agriculture, chemical sensing, and autonomous systems. However, conventional approaches collect dense spectral-spatial information and digitally process it into scene recognition, which causes a data bottleneck, limiting power efficiency, frame rate, and spectral-spatial resolution.