Abstract: A method for estimating an information unit represented by DNA strands, the method includes (a) sequencing the DNA strands to provide noisy copies of an encoded version of the information unit; wherein the information unit comprises information unit elements; (b) neural network (NN) processing the multiple noisy copies by one or more NNs to provide a soft estimate of the encoded information unit; wherein the soft estimate comprises estimated encoded information unit elements and an encoded information unit elements estimated confidence parameter; and (c) decoding the soft estimate of the encoded information unit to provide a prediction of the information unit.

Abstract: A method and system for segmenting free space area, in real-time, based on data from an electromagnetic device may include: an image acquisition device adapted to capture an image of a scene; an electromagnetic device adapted to produce data corresponding to the scene; a non-transitory memory device, wherein modules of instruction code may be stored; and a processor, associated with the memory device, and configured to execute the modules of instruction code. Upon execution of said modules of instruction code, the processor may be configured to train a module to perceive elements in a scene.

Abstract: A system and method for improving a resolution of a system may include providing to the ML module a set of input electromagnetic signals from an array included in a system; and improving, by the ML module, the resolution of the system by generating and providing at least one additional electromagnetic signal, based on the received set.

Abstract: A method and system for segmenting free space area, in real-time, based on data from an electromagnetic device may include: an image acquisition device adapted to capture an image of a scene; an electromagnetic device adapted to produce data corresponding to the scene; a non-transitory memory device, wherein modules of instruction code may be stored; and a processor, associated with the memory device, and configured to execute the modules of instruction code. Upon execution of said modules of instruction code, the processor may be configured to train a module to perceive elements in a scene.

Abstract: A system and a method for training a machine learning (ML) model to enhance a performance of an electromagnetic (EM) sensor, the method including: receiving one or more first data elements pertaining to a first signal of an EM sensor having a first performance parameter value; receiving one or more second data elements pertaining to a second signal of a data generator having a second performance parameter value; and training the ML model to generate a third signal, using the one or more first data elements as a training data set and using the one or more second data elements as supervisory data, where the third signal is characterized by a third performance parameter value that is higher than the first performance parameter value.

Abstract: A method and a system for training a machine-learning model to identify real-world elements using a simulated environment (SE) may include (a) receiving at least one set of appearance parameters, corresponding to appearance of real-world element; (b) generating one or more realistic elements, each corresponding to a variant of at least one real-world element; (c) generating one or more abstract-elements; (d) placing the elements within the SE; (e) producing at least one synthetic image from the SE; (f) providing the at least one synthetic image to a machine-learning model; and (g) training the machine-learning model to identify at least one real-world element from the at least one synthetic image, that corresponds to at least one realistic element in the SE.