公开(公告)号：US20220326909A1

公开(公告)日：2022-10-13

申请号：US17714327

申请日：2022-04-06

申请人： TEXAS INSTRUMENTS INCORPORATED

发明人： Anshu JAIN ,  Kumar DESAPPAN

IPC分类号： G06F7/499 ,  G06F7/483 ,  G06F5/01

摘要： A technique for bit depth up-conversion including obtaining an input value for a computation in a first bit depth with a fewer number of bits as compared to a second bit depth, converting the input value from the first bit depth to the second bit depth as an unsigned data value, adjusting a pointer to the converted input value based on the first bit depth, performing the computation based on the adjusted pointer to obtain an adjusted output value, and performing a right shift operation on the adjusted output value based on the first bit depth to obtain an output value.

公开(公告)号：US20200272892A1

公开(公告)日：2020-08-27

申请号：US16797871

申请日：2020-02-21

申请人： TEXAS INSTRUMENTS INCORPORATED

发明人： Kumar DESAPPAN ,  Mihir Narendra MODY ,  Pramod Kumar SWAMI ,  Anshu JAIN ,  Rishabh GARG

IPC分类号： G06N3/063 ,  G06N3/08 ,  G06F12/0804 ,  G06T1/60

摘要： Techniques including receiving a first set of values for processing by a machine learning (ML) network, storing a first portion of the first set of values in an on-chip memory, processing the first portion of the first set of values in a first layer of the ML network to generate a second portion of a second set of values, overwriting the stored first portion with the generated second portion, processing the second portion in a second layer of the ML network to generate a third portion of a third set of values, storing the third portion, repeating the steps of storing the first portion, processing the first portion, overwriting the stored first portion, processing the second portion, and storing the third portion for a fourth portion of the first set of values until all portions of the first set of values are processed to generate the third set of values.

公开(公告)号：US20240153105A1

公开(公告)日：2024-05-09

申请号：US18414772

申请日：2024-01-17

申请人： TEXAS INSTRUMENTS INCORPORATED

发明人： Deepak Kumar PODDAR ,  Anshu JAIN ,  Desappan KUMAR ,  Pramod Kumar SWAMI

IPC分类号： G06T7/246

CPC分类号： G06T7/246 ,  G06T2200/28 ,  G06T2207/20016 ,  G06T2207/30241

摘要： A method for sparse optical flow based tracking in a computer vision system is provided that includes detecting feature points in a frame captured by a monocular camera in the computer vision system to generate a plurality of detected feature points, generating a binary image indicating locations of the detected feature points with a bit value of one, wherein all other locations in the binary image have a bit value of zero, generating another binary image indicating neighborhoods of currently tracked points, wherein locations of the neighborhoods in the binary image have a bit value of zero and all other locations in the binary image have a bit value of one, and performing a binary AND of the two binary images to generate another binary image, wherein locations in the binary image having a bit value of one indicate new feature points detected in the frame.

公开(公告)号：US20220012635A1

公开(公告)日：2022-01-13

申请号：US17327869

申请日：2021-05-24

申请人： Texas Instruments Incorporated

发明人： Rishabh GARG ,  Pramod Kumar SWAMI ,  Kumar DESAPPAN ,  Anshu JAIN

IPC分类号： G06N20/00 ,  G06K9/62 ,  G06F11/30

摘要： Techniques for enhancing machine learning (ML) model execution. The technique includes determining an amount of memory used to process layers of a machine learning network having multiple layers, smoothing the amount of memory used to process the layers of the machine learning network based on a number of layers, identifying change layers where the smoothed amount of memory used changes more than a memory change threshold amount, grouping the layers of the machine learning network into a first layer grouping based on the identified change layers, and outputting the first layer grouping.