公开(公告)号：US20250037481A1

公开(公告)日：2025-01-30

申请号：US18437467

申请日：2024-02-09

Applicant: Intel Corporation

Inventor： Rita Chattopadhyay ,  Atul Divekar

IPC: G06V20/64 ,  G06V10/771 ,  G06V10/82

Abstract: Example systems, apparatus, articles of manufacture, and methods to detect and locate objects in three-dimensional (3D) point clouds are disclosed. Examples apparatus disclosed herein apply at least one of a template or a mask at a sample point of an overhead view of a 3D point cloud to identify a candidate cluster of points in the 3D point cloud, the candidate cluster to satisfy an occupancy target. Disclosed example apparatus also input the candidate cluster to a neural network, the neural network trained to output a feature vector for the candidate cluster. Disclosed example apparatus further process the feature vector to output parameters associated with an object classification and a bounding box for an object corresponding to the candidate cluster.

公开(公告)号：US20240151855A1

公开(公告)日：2024-05-09

申请号：US18281244

申请日：2022-03-21

Applicant: Intel Corporation

Inventor： Rita Chattopadhyay ,  Jun Cao

IPC: G01S17/931 ,  G01S7/48 ,  G01S17/46 ,  G01S17/89

CPC classification number: G01S17/931 ,  G01S7/4808 ,  G01S17/46 ,  G01S17/89

Abstract: Various systems and methods for implementing LiDAR-based object tracking described herein. An object tracking system for a vehicle includes an interface to communicate with object detection circuitry and an object similarity calculator circuitry, to obtain segmented data of an environment the object tracking system is operating within, the segmented data obtained using a light imaging detection and ranging (LiDAR) system, and the segmented data including a first plurality of segments detected in a first frame and a second plurality of segments detected in a second frame, the second frame captured after the first frame; determine, for a given segment of the first plurality of segments, a similar segment in the second plurality of segments; assign an VEHICLE object identification of the given segment to the similar segment; and track the similar segment from the first frame to the second frame based on the object identification.

公开(公告)号：US11747444B2

公开(公告)日：2023-09-05

申请号：US16103674

申请日：2018-08-14

Applicant: Intel Corporation

Inventor： Rita Chattopadhyay ,  Monica Lucia Martinez-Canales

IPC: G01S7/48 ,  G01S17/42 ,  G06N20/00 ,  G01S17/89 ,  G01S17/86 ,  G01S17/931

CPC classification number: G01S7/4802 ,  G01S17/42 ,  G01S17/86 ,  G01S17/89 ,  G01S17/931 ,  G06N20/00

Abstract: Various systems and methods for implementing LiDAR-based object detection and classification are described herein. An object detection system includes a feature extraction and object identification (FEOI) circuit to: receive segmented data of an environment around the object detection system, the segmented data obtained using a light imaging detection and ranging (LiDAR) system, oriented with respect to a direction of travel; compute spatial and structural parameters of a segment of the segmented data; and use the spatial and structural parameters with a machine learning model to obtain a classification of the segment.

公开(公告)号：US20230245452A1

公开(公告)日：2023-08-03

申请号：US18131783

申请日：2023-04-06

Applicant: Intel Corporation

Inventor： Say Chuan Tan ,  Mee Sim Lai ,  Ying Wei Liew ,  Chien Chern Yew ,  Kuan Heng Lee ,  Nicolas C. Galoppo von Borries ,  Rita Chattopadhyay

IPC: G06V20/40 ,  G06V20/52

CPC classification number: G06V20/44 ,  H04N23/667 ,  G06V20/52 ,  H04N23/695

Abstract: Embodiments of adaptive multi-modal event detection are disclosed herein. In one example, sensor data captured by multiple sensors is received, and an inconsistency among the sensors is detected based on performing event detection on the sensor data. An external environment of the sensors is detected based on the sensor data, and one or more configuration parameter(s) for event detection are adjusted based on the external environment of the sensors. Event detection is then performed on the sensor data based on the adjusted configuration parameter(s).

公开(公告)号：US20220126878A1

公开(公告)日：2022-04-28

申请号：US17434713

申请日：2020-03-27

Applicant: Intel Corporation

Inventor： Hassnaa Moustafa ,  Suhel Jaber ,  Darshan Iyer ,  Mehrnaz Khodam Hazrati ,  Pragya Agrawal ,  Naveen Aerrabotu ,  Petrus J. Van Beek ,  Monica Lucia Martinez-Canales ,  Patricia Ann Robb ,  Rita Chattopadhyay ,  Soila P. Kavulya ,  Karthik Reddy Sripathi ,  Igor Tatourian ,  Rita H. Wouhaybi ,  Ignacio J. Alvarez ,  Fatema S. Adenwala ,  Cagri C. Tanriover ,  Maria S. Elli ,  David J. Zage ,  Jithin Sankar Sankaran Kutty ,  Christopher E. Lopez-Araiza ,  Magdiel F. Galán-Oliveras ,  Li Chen

IPC: B60W60/00 ,  G05D1/00 ,  B60W50/14

Abstract: An apparatus comprising at least one interface to receive sensor data from a plurality of sensors of a vehicle; and one or more processors to autonomously control driving of the vehicle according to a path plan based on the sensor data; determine that autonomous control of the vehicle should cease; send a handoff request to a remote computing system for the remote computing system to control driving of the vehicle remotely; receive driving instruction data from the remote computing system; and control driving of the vehicle based on instructions included in the driving instruction data.

公开(公告)号：US10962966B2

公开(公告)日：2021-03-30

申请号：US16071889

申请日：2016-02-11

Applicant: Intel Corporation

Inventor： Petek Yontay ,  Rita Chattopadhyay

IPC: G05B23/02

Abstract: Apparatuses, methods and storage medium associated with monitoring or assisting in monitoring of an equipment process are disclosed herein. In embodiments, an apparatus may comprise an analyzer to: receive a plurality of simulation results of a plurality of control limit and alert zone combinations for potential use with a control chart to monitor the equipment process, and calculate a plurality of performance metrics for each of the plurality of control limit and alert zone combinations, using the plurality of simulation results. The apparatus may further select an optimal combination of control limits and alert zones, based at least in part on the plurality of performance metrics, and configure an equipment process monitor with the selected optimal combination of control limits and alert zones for use with a control chart to monitor the equipment process. Other embodiments may be described or claimed.

公开(公告)号：US10558897B2

公开(公告)日：2020-02-11

申请号：US15855763

申请日：2017-12-27

Applicant: Intel Corporation

Inventor： Vinod Sharma ,  Monica Lucia Martinez-Canales ,  Peggy Jo Irelan ,  Malini Krishnan Bhandaru ,  Rita Chattopadhyay ,  Soila Pertet Kavulya

IPC: G06K9/00 ,  G06K9/62 ,  G06K9/20 ,  G06K9/66

Abstract: Various systems and methods for implementing context-based digital signal processing are described herein. An object detection system includes a processor to: access sensor data from a first sensor and a second sensor integrated in a vehicle; access an operating context of the vehicle; assign a first weight to a first object detection result from sensor data of the first sensor, the first weight adjusted based on the operating context; assign a second weight to a second object detection result from sensor data of the second sensor, the second weight adjusted based on the operating context; and perform a combined object detection technique by combining the first object detection result weighted by the first weight and the second object detection result weighted by the second weight.

公开(公告)号：US10151475B2

公开(公告)日：2018-12-11

申请号：US14463401

申请日：2014-08-19

Applicant: Intel Corporation

Inventor： Rita Chattopadhyay ,  Hoang Van ,  Trevor Ryan ,  Paul Hough

IPC: F22B37/38 ,  G01M99/00

Abstract: The present disclosure is directed to a system for determining scaling in a boiler. At least one sensor may monitor a boiler during operation and provide sensor data to a boiler monitoring module including a boiler scaling determination module that may determine an amount of scaling in the boiler. Example sensor data may comprise power input, a temperature of liquid in the boiler and an air temperature within an enclosure housing the boiler. The boiler monitoring module may determine thermal energy transfer to the boiler based on the liquid and enclosure temperatures. A machine learning engine may determine a rate of thermal energy transfer to the liquid in view of the power input, the rate of thermal energy transfer being evaluated by the machine learning engine to identify delay in the rate of thermal energy transfer that quantifies an amount of scaling in the boiler.

公开(公告)号：US20180107936A1

公开(公告)日：2018-04-19

申请号：US15476487

申请日：2017-03-31

Applicant: Intel Corporation

Inventor： Rita Chattopadhyay ,  Kalpana A. Algotar ,  Ali Ashrafi ,  John Pilkin

IPC: G06N7/00 ,  A63B24/00

CPC classification number: G06N7/005 ,  A63B24/0062 ,  G16H20/30 ,  G16H50/20 ,  G16H50/30

Abstract: A disclosed example method to predict an injury for a target player on a target date includes determining a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determining a second probability of injury of the target player based on injuries of the target player; determining a third probability of injury of the target player based on the first probability of injury of the target player and the second probability of injury of the target player; and generating, by executing an instruction with the processor, a report of a predicted probability of injury of the target player for the target date based on the third probability of injury of the target player.

公开(公告)号：US09767671B2

公开(公告)日：2017-09-19

申请号：US14533434

申请日：2014-11-05

Applicant: Intel Corporation

Inventor： Rita Chattopadhyay

IPC: G08B23/00 ,  G08B21/18 ,  G08B25/08 ,  G08B13/14 ,  H04Q5/22 ,  G01C25/00

CPC classification number: G08B21/187 ,  G01F25/0061 ,  G01F25/0076 ,  G01F25/0084 ,  G08B25/08

Abstract: The present disclosure is directed to a system for determining sensor condition. A sensor signal generated by a sensor to communicate the current condition of an aspect being monitored by the sensor may also be employed to determine the condition of the sensor itself. For example, a device capable of determining if the sensor condition is normal or malfunctioning (e.g., erratic, stuck, etc.) may comprise a monitoring module (MM) to receive the sensor signal. The MM may comprise a sensor condition determination module (SCDM) to determine sensor condition. The SCDM may include a feature extraction engine to determine various characteristics of (e.g., to “extract features” from) the sensor signal and a model to determine sensor condition based on the extracted features. The model may include a support vector machine (SVM) taught to determine sensor condition utilizing sampled sensor signals correlated with annotations of sensor condition.