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公开(公告)号：US20240086681A1
公开(公告)日：2024-03-14
申请号：US18389336
申请日：2023-11-14
Applicant: Texas Instruments Incorporated
Inventor： Mihir Narendra Mody , Veeramanikandan Raju , Chaitanya Ghone , Deepak Poddar
CPC classification number: G06N3/04 , G06N3/045 , G06N3/088 , H04L63/0435 , H04L63/0464
Abstract: A CNN based-signal processing includes receiving of an encrypted output from a first layer of a multi-layer CNN data. The received encrypted output is subsequently decrypted to form a decrypted input to a second layer of the multi-layer CNN data. A convolution of the decrypted input with a corresponding decrypted weight may generate a second layer output, which may be encrypted and used as an encrypted input to a third layer of the multi-layer CNN data.
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公开(公告)号：US11288525B2
公开(公告)日：2022-03-29
申请号：US16588157
申请日：2019-09-30
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Deepak Poddar , Soyeb Nagori , Manu Mathew , Debapriya Maji
Abstract: Techniques including receiving a distorted image from a camera disposed about a vehicle, detecting, in the distorted image, corner points associated with a target object, mapping the corner points to a distortion corrected domain based on one or more camera parameters, mapping the corner points and lines between the corner points back to a distorted domain based on the camera parameters, interpolating one or more intermediate points to generate lines between the corner points in the distortion corrected domain mapping the corner points and the lines between the corner points back to a distorted domain based on the camera parameters, and adjusting a direction of travel of the vehicle based on the located target object.
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公开(公告)号：US20240338253A1
公开(公告)日：2024-10-10
申请号：US18361401
申请日：2023-07-28
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Pramod Swami , Mihir Mody , Deepak Poddar
IPC: G06F9/50
CPC classification number: G06F9/5038
Abstract: Various examples disclosed herein relate to digital signal processing, and more particularly, to processing stages of multi-channel processing pipelines in batches according to an order. A method of such processing is provided and includes retrieving multi-channel data from a memory and processing the multi-channel data with a hardware accelerator implementing a multi-stage processing pipeline for each channel of a plurality of channels. The multi-stage processing pipelines can be arranged in a cyclically descending order based on a total number of stages of each multi-stage processing pipeline. Processing the multi-channel data includes sequentially processing a plurality of batches each including one or more stages from different multi-stage processing pipelines adjacent to each other in the cyclically descending order. Processing the plurality of batches may include processing corresponding ones of the stages in parallel.
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公开(公告)号：US20220147748A1
公开(公告)日：2022-05-12
申请号：US17512049
申请日：2021-10-27
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Soyeb Nagori , Deepak Poddar
Abstract: Various embodiments of the present technology relate to using neural networks to detect objects in images. More specifically, some embodiments relate to the reduction of computational analysis regarding object detection via neural networks. In an embodiment, a method of performing object detection is provided. The method comprises determining, via a convolution neural network, at least a classification of an image, wherein the classification corresponds to an object in the image and comprises location vectors corresponding to pixels of the image. The method also comprises, for at least a location vector of the location vectors, obtaining a confidence level, wherein the confidence level represents a probability of the object being present at the location vector, and calculating an upper-bound score based at least on the confidence level. The method further comprises, for at least an upper-bound score based at least on the confidence level, performing an activation function on the upper-bound score, and classifying, via a detection layer, the object in the image.
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公开(公告)号：US20240153139A1
公开(公告)日：2024-05-09
申请号：US18355594
申请日：2023-07-20
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Debapriya Maji , Soyeb Nagori , Deepak Poddar , Manu Mathew
IPC: G06T7/73
CPC classification number: G06T7/75 , G06T2207/20081 , G06T2207/20084
Abstract: Disclosed herein are systems and methods that provide an end-to-end approach for performing multi-dimensional object pose estimation in the context of machine learning models. In an implementation, processing circuitry of a suitable computer inputs image data to a machine learning model that predicts a parameterized rotation vector and a parameterized translation vector for an object in the image. Next, the processing circuitry converts the parameterized rotation vector and the parameterized translation vector into a non-parameterized rotation vector and a non-parameterized translation vector respectively. Finally, the processing circuitry updates the image data based on the non-parameterized rotation vector and the non-parameterized translation vector.
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Patent Agency Ranking
公开(公告)号：US11891091B2
公开(公告)日：2024-02-06
申请号：US18172495
申请日：2023-02-22
Applicant: Texas Instruments Incorporated
Inventor： Soyeb Noormohammed Nagori , Deepak Poddar , Hrushikesh Tukaram Garud
CPC classification number: B60W60/0015 , G05D1/0223 , G05D1/0246 , G05D1/0278 , G06F18/2163 , G06V10/764 , G06V10/82 , G06V20/58 , G05D2201/0213
Abstract: An example driver assistance system includes an object detection (OD) network, a semantic segmentation network, a processor, and a memory. In an example method, an image is received and stored in the memory. An object detection (OD) polygon is generated for each object detected in the image, and each OD polygon encompasses at least a portion of the corresponding object detected in the image. A region of interest (ROI) is associated with each OD polygon. Such method may further comprise generating a mask for each ROI, each mask configured as a bitmap approximating a size of the corresponding ROI; generating at least one boundary polygon for each mask based on the corresponding mask, each boundary polygon having multiple vertices and enclosing the corresponding mask; and reducing a number of vertices of the boundary polygons based on a comparison between points of the boundary polygons and respective points on the bitmaps.
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公开(公告)号：US20200250485A1
公开(公告)日：2020-08-06
申请号：US16784009
申请日：2020-02-06
Applicant: Texas Instruments Incorporated
Inventor： Soyeb Noormohammed Nagori , Deepak Poddar , Hrushikesh Tukaram Garud
Abstract: In described examples, an apparatus includes an object detection (OD) network that is configured to generate OD polygons in response to a received at least one camera image and a semantic segmentation (SS) network that is configured to generate SS data in response to the received at least one camera image. A processor is configured to generate an updated occupancy grid in response to the OD polygons and the SS data. A vehicle is optionally configured to respond to a driving action generated in response to the updated occupancy grid.
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公开(公告)号：US11620478B2
公开(公告)日：2023-04-04
申请号：US16784009
申请日：2020-02-06
Applicant: Texas Instruments Incorporated
Inventor： Soyeb Noormohammed Nagori , Deepak Poddar , Hrushikesh Tukaram Garud
Abstract: In described examples, an apparatus includes an object detection (OD) network that is configured to generate OD polygons in response to a received at least one camera image and a semantic segmentation (SS) network that is configured to generate SS data in response to the received at least one camera image. A processor is configured to generate an updated occupancy grid in response to the OD polygons and the SS data. A vehicle is optionally configured to respond to a driving action generated in response to the updated occupancy grid.
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公开(公告)号：US11417017B2
公开(公告)日：2022-08-16
申请号：US16854590
申请日：2020-04-21
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Hrushikesh Tukaram Garud , Deepak Poddar , Soyeb Noormohammed Nagori
Abstract: Techniques for localizing a vehicle including obtaining an image from a camera, identifying a set of image feature points in the image, obtaining an approximate location of the vehicle, determining a set of sub-volumes (SVs) of a map to access based on the approximate location, obtaining map feature points and associated map feature descriptors associated with the set of SVs, determining a set of candidate matches between the set of image feature points and the obtained map feature points, determining a set of potential poses of the camera from candidate matches from the set of candidate matches and an associated reprojection error estimated for remaining points to select a first pose of the set of potential poses having a lowest associated reprojection error, determining the first pose is within a threshold value of an expected vehicle location, and outputting a vehicle location based on the first pose.
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公开(公告)号：US20200293859A1
公开(公告)日：2020-09-17
申请号：US16889853
申请日：2020-06-02
Applicant: Texas Instruments Incorporated
Inventor： Mihir Narendra Mody , Veeramanikandan Raju , Chaitanya Ghone , Deepak Poddar
Abstract: A CNN based-signal processing includes receiving of an encrypted output from a first layer of a multi-layer CNN data. The received encrypted output is subsequently decrypted to form a decrypted input to a second layer of the multi-layer CNN data. A convolution of the decrypted input with a corresponding decrypted weight may generate a second layer output, which may be encrypted and used as an encrypted input to a third layer of the multi-layer CNN data.
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