公开(公告)号：US20240080423A1

公开(公告)日：2024-03-07

申请号：US18057126

申请日：2022-11-18

Applicant: Samsung Electronics Co., Ltd.

Inventor： Wenbo Li ,  Zhipeng Mo ,  Yi Wei ,  Burak Uzkent ,  Qian Lou ,  Yilin Shen ,  Hongxia Jin

IPC: H04N9/64

CPC classification number: H04N9/64

Abstract: A method includes obtaining raw image data, where the raw image data includes data values each having most significant bits and least significant bits. The method also includes providing the raw image data to a trained machine learning model and generating processed image data using the trained machine learning model. The method further includes presenting an image based on the processed image data. The trained machine learning model is trained to modulate a feature map associated with the most significant bits of the data values of the raw image data based on the least significant bits of the data values of the raw image data in order to generate a fusion of the most significant bits and the least significant bits of the data values of the raw image data.

公开(公告)号：US20230177338A1

公开(公告)日：2023-06-08

申请号：US18073383

申请日：2022-12-01

Applicant: Samsung Electronics Co., Ltd.

Inventor： Qian Lou ,  Yen-Chang Hsu ,  Burak Uzkent ,  Ting Hua ,  Yilin Shen ,  Hongxia Jin

IPC: G06N3/082 ,  G06V10/82 ,  G06V10/772

CPC classification number: G06N3/082 ,  G06V10/82 ,  G06V10/772

Abstract: A method includes obtaining, using a first electronic device, a weight matrix associated with a trained transformer model. The method also includes factorizing the weight matrix into a dictionary weight matrix and an intermediate matrix. The method further includes pruning the intermediate matrix to generate a sparse intermediate matrix. The method also includes fine-tuning the sparse intermediate matrix based on a training dataset to generate a fine-tuned sparse intermediate matrix. The method further includes determining an index matrix and a coefficient matrix based on the fine-tuned sparse intermediate matrix. In addition, the method includes deploying the dictionary weight matrix, the index matrix, and the coefficient matrix to a second electronic device without deploying the weight matrix to the second electronic device. A number of parameters in the dictionary weight matrix, the index matrix, and the coefficient matrix is smaller than a number of parameters in the weight matrix.