Patent ID: 11907835
Assignee: YEDA RESEARCH AND DEVELOPMENT CO. LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer implemented method for performing a task on a specific single test signal; the task is at least one selected from: super-resolution, deblurring, denoising, completion of missing data, distortion correction, correcting compression artifacts, dehazing, signal-enhancement, signal-manipulation, and degradation removal; the method comprising:
constructing a signal-specific deep learning neural network (DLNN), by selecting number of nodes, number of layers, and their inter connections, configured for said task and said specific single test signal;
generating training target outputs from said specific single test signal, via transformations thereof;
generating a corresponding training input for each of said training target outputs, by degrading said training target outputs;
training said DLNN to perform said task, using a training set comprising pairs of said training target outputs and their said corresponding training inputs, whereby the DLNN is trained to perform said task only on said specific single test signal and signals originated therefrom; and
applying said trained DLNN on said specific single test signal, wherein said specific single test signal is provided as an input to said trained DLNN, to obtain an output signal in accordance with said task.