We invented a non-destructive terahertz (THz) deep-learning computed tomography system based on time-domain spectroscopy. In the method, THz time-domain signals are profiled. Multiple features are retrieved from those profiles by a trained modeltransformed to the spatial domain to reconstruct a cross-sectional tomographic image. We have also invented a 3D THz tomographic system based on multi-scale spatio-spectral feature fusion in a multi-scale manner. We believe our work will stimulate further applicable research of THz tomographic imaging with advanced computer vision techniques.

Based on the optical fluorescence of the plant, the technology distinguishes the difference of the main protein infected by virus from the normal ones with the feature light. The main difference of this technology is to omit the complicatedbiochemical-material- consumption procedures. With the establishment of big data, the artificial intelligence algorithm identifies whether the implant is.