US 12,438,555 B2
Quality of lossy compressed sensor data with machine learning
Vinicius Michel Gottin, Rio de Janeiro (BR); Rômulo Teixeira de Abreu Pinho, Niterói (BR); Eduardo Vera Sousa, Niterói (BR); Alex Laier Bordignon, Niterói (BR); Paulo de Figueiredo Pires, Niterói (BR); and Franklin Ventura, Niterói (BR)
Assigned to Dell Products L.P., Round Rock, TX (US)
Filed by Dell Products L.P., Round Rock, TX (US)
Filed on Jan. 23, 2023, as Appl. No. 18/158,107.
Prior Publication US 2024/0250696 A1, Jul. 25, 2024
Int. Cl. H03M 7/00 (2006.01); H03M 7/30 (2006.01)
CPC H03M 7/6005 (2013.01) [H03M 7/3059 (2013.01); H03M 7/3082 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, at a reconstruction engine over a network, a sequence of lossy compression data that has been generated at a device, wherein the sequence of lossy compression data was generated by compressing a sequence of data with a lossy compression operation;
decompressing the lossy compression data to generate decompressed data;
providing the lossy compression data, the decompressed data, and at least one past sequence as input to a reconstruction model associated with the reconstruction engine to generate a residue that is configured to reduce a distance between the decompressed data and the sequence of data; and
generating corrected decompressed data by combining the decompressed data with the residue.